Senior data scientist jobs in Missouri City, TX - 223 jobs

Summary/Objective Alliance Technical Group is seeking an experienced Senior Data Engineer to design, build, and optimize the databases and data systems that power our business intelligence and analytics platforms. In this role, you will lead the creation of scalable pipelines, data models, and cloud-based architecture that ensures reliable, high-quality data across the organization. You will architect and implement new database solutions, drive migration and optimization efforts in PostgreSQL and Snowflake, and advance data governance initiatives. Working in an agile, cross-functional environment, you will translate business needs into scalable solutions while ensuring security, integrity, and performance. This role is ideal for someone who thrives on building data platforms from the ground up and shaping enterprise data strategy. This position is remote but may follow a hybrid schedule for candidates located within 60 miles of an Alliance office. Essential Functions Architect and implement new databases and data platforms to meet business and technical requirements Build and maintain scalable ELT/ETL pipelines and data models for analytics and reporting Manage and optimize database environments, including provisioning, performance tuning, and access controls Implement and manage automation and workflow orchestrations for reliable, repeatable deployments Ensure data quality, consistency, and compliance through robust validation and monitoring practices Collaborate with cross-functional teams to define technical requirements, estimate development efforts, and deliver business-aligned solutions Troubleshoot complex issues, recommend improvements, and maintain clear documentation of data systems, processes, and solutions proposed/implemented Mentor junior data engineers, providing technical guidance, code reviews, and best practices Required Qualifications Bachelor's degree in Computer Science, Information Systems, or related field (or equivalent experience) 10+ years of hands-on experience with relational databases, including designing and implementing new database systems Knowledge, Skills, & Abilities Proven experience designing and building new databases and large-scale data systems, particularly in PostgreSQL and Snowflake; hands-on experience with dbt Demonstrated ability to develop and optimize ELT/ETL pipelines for complex data sets Experience with cloud architecture, workflow orchestration, and Git-based version control Knowledge of data governance, data quality, and validation practices Strong troubleshooting and root-cause analysis skills Excellent communication skills and experience working in agile, cross-functional teams Working knowledge of Python preferred, familiarity with data visualization principles a plus Work Environment While performing the duties of this job, the employee regularly works in an office setting with constant sitting and occasional standing. Physical Demands Prolonged periods of sitting or standing at a desk while using a computer. Travel Not Applicable Other Duties Please note this job description is intended to describe the general nature and level of work performed by employees assigned to this position. It is not designed to contain or be interpreted as a comprehensive list of all duties, responsibilities, and qualifications. Additional job-related duties may be assigned. Alliance reserves the right to amend and change responsibilities to meet business and organizational needs as necessary with or without notice. Employee Benefits: Key Benefits Include: - Medical, Dental, and Vision Insurance - Flexible Spending Accounts - 401(K) Plan with Competitive Match - Continuing Education and Tuition Assistance - Employer-Sponsored Disability Benefits - Life Insurance - Employee Assistance Program (EAP) - Paid Time Off (PTO), Paid Holidays, & Bonus Floating Holiday (if hired before July 1st) - Profit Sharing or Individual Bonus Programs - Referral Program - Per Diem & Paid Travel - Employee Discount Hub Salary based upon experience. EEO Commitment: We are an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, national origin, ethnicity, sex, pregnancy, sexual orientation, gender identity/expression, including transgender identity, religion, disability, age, genetics, active military or veteran status and any other characteristics protected under applicable federal or state law.

Living Our Values All associates are guided by Our Values. Our Values are the unifying foundation of our companies. We strive to ensure that every decision we make and every action we take demonstrates Our Values. We believe that putting Our Values into practice creates lasting benefits for all of our associates, shareholders, and the communities in which we live. Why Join Us Career Growth: Advance your career with opportunities for leadership and personal development. Culture of Excellence: Be part of a supportive team that values your input and encourages innovation. Competitive Benefits: Enjoy a comprehensive benefits package that looks after both your professional and personal needs. Total Rewards Our Total Rewards package underscores our commitment to recognizing your contributions. We offer a competitive and fair compensation structure that includes base pay and performance-based rewards. Compensation is based on skill set, experience, qualifications, and job-related requirements. Our comprehensive benefits package includes medical, dental, and vision insurance, wellness programs, retirement plans, and generous paid leave. Discover more about what we offer by visiting our Benefits page. A Day In The Life As a Lead Data Engineer within the Trailblazer initiative, you will play a crucial role in architecting, implementing, and managing robust, scalable data infrastructure. This position demands a blend of systems engineering, data integration, and data analytics skills to enhance TFG's data capabilities, supporting advanced analytics, machine learning projects, and real-time data processing needs. The ideal candidate brings deep expertise in Lakehouse design principles, including layered Medallion Architecture patterns (Bronze, Silver, Gold), to drive scalable and governed data solutions. This is also a highly visible leadership role that will represent the data engineering function and lead the Data Management Community of Practice across TFG. As a Lead Data Engineer you will: Design and implement scalable and reliable data pipelines to ingest, process, and store diverse data at scale, using technologies such as Apache Spark, Hadoop, and Kafka. Work within cloud environments like AWS or Azure to leverage services including but not limited to EC2, RDS, S3, Lambda, and Azure Data Lake for efficient data handling and processing. Architect and operationalize data pipelines following Medallion Architecture best practices within a Lakehouse framework-ensuring data quality, lineage, and usability across Bronze, Silver, and Gold layers. Develop and optimize data models and storage solutions (Databricks, Data Lakehouses) to support operational and analytical applications, ensuring data quality and accessibility. Utilize ETL tools and frameworks (e.g., Apache Airflow, Fivetran) to automate data workflows, ensuring efficient data integration and timely availability of data for analytics. Lead the Data Management Community of Practice, serving as the primary facilitator, coordinator, and spokesperson. Drive knowledge sharing, establish best practices, and represent the data engineering discipline across TFG to both technical and business audiences. Collaborate closely with data scientists, providing the data infrastructure and tools needed for complex analytical models, leveraging Python or R for data processing scripts. Ensure compliance with data governance and security policies, implementing best practices in data encryption, masking, and access controls within a cloud environment. Monitor and troubleshoot data pipelines and databases for performance issues, applying tuning techniques to optimize data access and throughput. Stay abreast of emerging technologies and methodologies in data engineering, advocating for and implementing improvements to the data ecosystem. What We Need From You Bachelor's Degree in Computer Science, MIS, or other business discipline and 10+ years of experience in data engineering, with a proven track record in designing and operating large-scale data pipelines and architectures Req or Master's Degree computer science, MIS, or other business discipline and 5+ years of experience in data engineering, with a proven track record in designing and operating large-scale data pipelines and architectures Req Demonstrated experience designing and implementing Medallion Architecture in a Databricks Lakehouse environment, including layer transitions, data quality enforcement, and optimization strategies. Required Expertise in developing ETL/ELT workflows Required Comprehensive knowledge of platforms and services like Databricks, Dataiku, and AWS native data offerings Required Solid experience with big data technologies (Apache Spark, Hadoop, Kafka) and cloud services (AWS, Azure) related to data processing and storage Required Strong experience in AWS cloud services, with hands-on experience in integrating cloud storage and compute services with Databricks Required Proficient in SQL and programming languages relevant to data engineering (Python, Java, Scala) Required Hands on RDBMS experience (data modeling, analysis, programming, stored procedures) Required Familiarity with machine learning model deployment and management practices is a plus Required Strong executive presence and communication skills, with a proven ability to lead communities of practice, deliver presentations to senior leadership, and build alignment across technical and business stakeholders. Required AWS Certified Solution Architect Preferred Databricks Certified Associate Developer for Apache Spark Preferred DAMA CDMP Preferred or other relevant certifications. Preferred Physical and Environmental RequirementsThe physical requirements described here are representative of those that must be met by an associate to successfully perform the essential functions of the job. While performing the duties of the job, the associate is required on a daily basis to analyze and interpret data, communicate, and remain in a stationary position for a significant amount of the work day and frequently access, input, and retrieve information from the computer and other office productivity devices. The associate is regularly required to move about the office and around the corporate campus. The associate must frequently move up to 10 pounds and occasionally move up to 25 pounds. Travel Requirements 20% The associate is occasionally required to travel to other sites, including out-of-state, where applicable, for business. Join Us The Friedkin Group and its affiliates are committed to ensuring equal employment opportunities, including providing reasonable accommodations to individuals with disabilities. If you have a disability and would like to request an accommodation, please contact us at . We celebrate diversity and are committed to creating an inclusive environment for all associates. We are seeking candidates legally authorized to work in the United States, without Sponsorship. #LI-BM1

*To access Dayforce at its best, log in from the latest version of Chrome, Safari, Firefox, or Edge. * Boardwalk is a limited partnership operating in the midstream portion of the natural gas and natural gas liquids industry, providing transportation and storage services for our customers. Our 14,000 miles of pipeline and storage assets provide diverse market connectivity to producers and end-users who need reliable sources of natural gas for power generation, home heating or petrochemical feedstocks. We have the experience, knowledge, and flexibility to design service offerings and create system enhancements tailored to our customers' needs throughout the 13 states in which we operate. As an organization focused on sustainability, we are committed to protecting the environment while delivering this energy source. This commitment is made to our customers, employees, and the communities in which we operate. We incorporate environmental stewardship, safety, and compliance into our day-to-day operations and seek to strengthen and support the communities we serve. Additional information about the company can be found online at ******************** We are currently looking for a Data Scientist I/ II/ Sr for our Houston, TX office. POSITION DESCRIPTION: The Data Scientist plays a key role in advancing digital innovation by developing data-driven models and insights that support operational efficiency, asset optimization, and strategic decision-making. This role will work closely with data engineers, business stakeholders, and digital leadership to design and deploy machine learning (ML) models, predictive analytics, and advanced visualizations that drive measurable business outcomes. The ideal candidate combines strong analytical skills with deep technical expertise in cloud-based data science tools, particularly within the Amazon Web Services (AWS) ecosystem. This role requires a passion for solving complex problems, a collaborative mindset, and the ability to translate data into actionable insights for a midstream energy environment. KEY RESPONSIBILITIES Model Development & Advanced Analytics Design, build, and deploy predictive models and machine learning (ML) algorithms to support asset performance, reliability, and commercial optimization. Conduct exploratory data analysis (EDA), feature engineering, and statistical modeling using Python, R, or similar tools. Develop time series forecasting, anomaly detection, and classification models for operational and business use cases. Apply geospatial and sensor data analytics to support pipeline monitoring, flow optimization, and risk assessment. Cloud & Platform Integration Leverage Amazon Web Services (AWS) tools such as SageMaker, Redshift, Simple Storage Service (S3), Lambda, and Glue for model training, deployment, and data access. Collaborate with data engineers to ensure models are integrated into production pipelines and dashboards. Use version control (e.g., Git) and continuous integration/continuous deployment (CI/CD) practices to manage model lifecycle and reproducibility. Business Collaboration & Impact Partner with operations, engineering, and commercial teams to identify high-impact use cases and translate business needs into analytical solutions. Present findings and recommendations through compelling data visualizations and storytelling using tools like Power BI or Tableau. Support the development of self-service analytics and promote data literacy across the organization. Document model assumptions, limitations, and performance metrics to ensure transparency and trust. Model Governance & Continuous Improvement Monitor model performance and retrain as needed to maintain accuracy and relevance. Implement MLOps practices to support scalable, automated model deployment and monitoring. Ensure compliance with data governance, privacy, and ethical AI standards. Stay current with industry trends and emerging technologies to continuously improve analytical capabilities. REQUIRED SKILLS, KNOWLEDGE, AND EXPERIENCE: Bachelor's or Master's degree in Data Science, Computer Science, Engineering, Statistics, or a related field. 3-5+ years of experience in applied data science, preferably in the energy, utilities, or industrial sectors. Proficiency in Python, SQL, and data science libraries such as pandas, scikit-learn, TensorFlow, or PyTorch. Experience working with AWS services including SageMaker, Redshift, S3, and Lambda. Strong understanding of statistical modeling, machine learning, and data visualization techniques. Ability to communicate complex technical concepts to non-technical stakeholders. Experience working with large datasets and real-time or near-real-time data environments. PREFERRED SKILLS, KNOWLEDGE, AND EXPERIENCE: Experience in the natural gas midstream or broader oil & gas industry. Familiarity with MLOps practices and tools for model monitoring and retraining. Exposure to geospatial data, sensor data, or SCADA systems. Experience with Power BI, Tableau, or similar BI tools. Knowledge of data governance, security, and compliance in cloud environments. REQUIRED EDUCATION: Bachelor's degree in Computer Science, Engineering, Statistics, or related field PREFERRED EDUCATION: Master's degree ADDITIONAL INFORMATION: Boardwalk Pipelines, LP, maintains a drug-free workplace and will require pre-employment drug & substance abuse testing before hire. Boardwalk Pipelines, LP is an equal opportunity employer. All applicants will be considered for employment regardless of race, color, religion, age, sex, gender identity, national origin, veteran, or disability status.

Department: IT - BI Finance/HCM/Ops Contract Months:12 Salary Range: $92,540.00 - $152,691.00 Academic Year: 25-26 The Senior Data Scientist - Strategic Data Intelligence leads advanced analytics, modeling, and predictive insights for Houston ISD's enterprise systems. This role focuses on data from Finance, Budgeting, Procurement, HR, and other ERP domains. The Senior Data Scientist works across departments to develop models that inform operational decision-making, forecast resource needs, and identify efficiency opportunities. The role plays a key part in ensuring HISD leverages Microsoft Fabric and Power BI to build intelligent, automated data tools that support a modern, cloud-based ERP landscape. MAJOR DUTIES & RESPONSIBILITIES 1. Build and maintain statistical and machine learning models using data from enterprise systems. 2. Partner with Finance, HR, Procurement, and Budgeting teams to understand strategic data needs. 3. Develop forecasts, classification models, or cluster analyses to optimize operations. 4. Create executive dashboards, simulations, and decision-support tools using Power BI and Microsoft Fabric. 5 Lead efforts to clean, normalize, and combine data from Oracle Fusion, legacy SAP, and other platforms. MAJOR DUTIES & RESPONSIBILITIES CONTINUED 6. Publish clear documentation and visual explanations of findings to both technical and non-technical audiences. 7. Collaborate with data engineers and architects to ensure models are reproducible and scalable. 8. Evaluate external datasets and economic indicators to enhance district forecasting. 9. Mentor other analysts and data professionals within the department. 10. Perform other job-related duties as assigned. EDUCATION Master's degree in data science, statistics, applied mathematics, or related quantitative field required. Ph.D. preferred. * Applicants who do not meet these education qualifications may be considered if they have a unique combination of education and work experiences that indicate potential for success in this role. WORK EXPERIENCE Minimum of 6 years in data science, analytics, or quantitative research. Experience with ERP or operational systems in education, government, or large enterprises preferred. SKILL AND/OR REQUIRED LICENSING/CERTIFICATION * Advanced experience with Python, R, or other statistical programming languages * Strong SQL and data modeling skills * Experience using Power BI and Microsoft Fabric for data analysis * Knowledge of ERP data structures (finance, HR, procurement) * Strong communication and data storytelling abilities * Preferred certifications: Microsoft Certified: Data Scientist Associate, Azure Data Scientist Associate LEADERSHIP RESPONSIBILITIES Serves as a senior contributor and thought leader within the Strategic Data Intelligence team. May lead projects or mentor junior analysts. WORK COMPLEXITY/INDEPENDENT JUDGMENT Applies independent judgment to solve complex, ambiguous problems. Chooses modeling approaches, variables, and algorithms based on context and stakeholder needs. BUDGET AUTHORITY May provide input on software, tools, or external data subscriptions needed to support modeling. PROBLEM SOLVING Translates large-scale, messy data into actionable insights and predictive tools. Identifies gaps and inefficiencies in data collection or usage. IMPACT OF DECISIONS Models and forecasts directly influence staffing, budgeting, procurement, and other enterprise decisions across HISD. COMMUNICATION/INTERACTIONS Presents models, insights, and scenarios to senior district leadership, department heads, and peer analysts. CUSTOMER RELATIONSHIPS Provides expert-level support to business units seeking to improve operations using predictive and statistical tools. WORKING/ENVIRONMENTAL CONDITIONS Office or hybrid setting. Extended screen time and data review required. May work long hours during major forecasting periods. Houston Independent School District is an equal opportunity employer.

Daikin Comfort Technologies Mfg is seeking a professional, skilled individual for our Data Scientist position at our Waller, TX facility. The Data Scientist role at its core links business strategy to the data. The Data Scientist role at its core links business strategy to the data. He/she will transform structured or unstructured data into actionable information and predictive models to make a big impact across the organization. This individual will break down the hairiest of problems by applying the full data science toolkit and provide insights to stakeholders across the organization to change minds and hearts. He/she will keep the customer front of mind in all of the work and optimize the customer experience, which will translate to creating long-term business value. As a pioneering Data Scientist at Daikin, he/she will influence the cultural change around how we use, talk about, and ultimately value our data assets, as part of a broader Digital Transformation. Why work with us? > Benefits are effective on day one for all full-time direct hires. > Training programs are available to help guide team members and develop new skills. > Growth Opportunities - there are immense opportunities to grow your career. > You will be part of a Global Company - our family brands are backed by Daikin Industries, Ltd. Position Responsibilities may include: Gather, process, clean, enrich, and integrate structured and unstructured data to build advanced models to turn data into insights; creatively analyze data to understand drivers of historical business performance and build predictive models to inform future business strategies Deep understanding of our organization's data structure; look for ways to improve to enhance our ability to perform robust data analysis; create new data sets when there is little or no data available, to inform marketing analysis Engage with third-party data providers to strengthen and enrich data models as needed; inform purchase of net new data Deeply understand all sources of data across the enterprise, link to data strategy, and continually evolve ability to measure and track key data points to enable data-driven decisions Collect and provide quantitative and qualitative information to measure effectiveness of marketing activities and answer strategic business questions Analyze and discern campaign execution, targeting and optimization of marketing investment to deliver sales and operating profit across brands Utilize visualization solutions to improve timeliness of data delivery and provide better visibility to decision makers to help them monitor, measure, or predict how the company is performing Perform marketing research & analysis to inform customer targeting & segmentation, in addition to longitudinal tracking of Customer Lifetime Value across the enterprise Assist with internal assessments of workflow processes to identify inefficiencies, especially those where Marketing is involved, and propose more efficient processes and procedures via process automation leveraging tech platforms Assist with maintenance and management of Marketing SQL database and Snowflake cloud data warehouse Provide data science support and ad hoc analysis to enterprise leadership as needed Perform additional projects/duties to support ongoing business needs. Nature & Scope: Applies practical knowledge of job area typically obtained through advanced education and work experience Encouraged to seek continuous improvements Performs a range of mainly straightforward assignments Works independently with general supervision Problems faced are difficult but not typically complex Knowledge & Skills: Strong analytical skills with attention to detail; strong knowledge of statistical analysis, machine learning process, computer science principles, and basic programming principles Moderate data storytelling ability - ability to produce actionable information/insights, not just data crunching Strong communication skills, both verbally and written, capable of communicating with people of many different levels of an organization Knowledge of experimentation and testing of Minimum Viable Products to determine if proposed business models / solutions scale up Proficient in MS Office especially Excel; ability to translate data insights into PowerPoint presentations Strong understanding of relational databases with experience in SQL - Microsoft SQL Server, Oracle, Postgres Moderate experience with A/B testing and data science techniques to build and implement predictive models Strong experience with visualization tools such as Tableau, Qlik, or Microsoft Power BI (or similar applications) Moderate experience with Python, R, Alteryx or other analytics platforms a plus (or similar applications) Eager to make a big impact at a large company - you show up for work and get things done Natural ability and desire to work on a team - goes the extra mile when needed; ability to work independently too Ability to grasp complex concepts and systems quickly Ability to manage multiple projects and shift direction quickly Intellectual curiosity and strong passion for using data to solve problems creatively Ability to apply good judgment, strong work ethic, and integrity on the job. Experience: 3-5 years of work experience in a Marketing / Consulting / Business Analyst / Data Science role Experience solving complex business problems involving a heavy amount of analytics / data science Marketing-based experience preferred, but not required (either D2C or B2B performance marketing) HVAC industry experience preferred, but not required Education/Certification: Bachelor's degree (required) in Marketing / Business / Engineering / Statistics / Mathematics / Economics / Computer Science; or other related degree with strong quantitative emphasis Master's degree (preferred) in Data Science / Business Administration / Marketing People Management: No Physical Requirements / Work Environment: Must be able to perform essential responsibilities with or without reasonable accommodations Reports To: Qualified Applicants must be legally authorized for employment in the United States. Qualified applicants will not require employer sponsored work authorization now or in the future for employment in the United States. The Company provides equal employment opportunity to all employees and applicants regardless of a person's race, color, religion (including religious dress or grooming practices), creed, national origin (including language use restrictions), citizenship, uniform service member or veteran status, ancestry, disability, physical or mental disability (including HIV/AIDS), medical condition (including cancer and genetic characteristics), genetic information, request for protected leave, marital status, sex, pregnancy, age (over 40), sexual orientation, gender, gender identity or expression, political affiliation, or any other characteristic protected by law. The Company will comply with all federal and state regulations and statutes pertaining to individuals with disabilities.

Argo Group International Holdings, Inc. and American National, US based specialty P&C companies, (together known as BP&C, Inc.) are wholly owned subsidiaries of Brookfield Wealth Solutions, Ltd. (“BWS”), a New York and Toronto-listed public company. BWS is a leading wealth solutions provider, focused on securing the financial futures of individuals and institutions through a range of wealth protection and retirement services, and tailored capital solutions. Job Description Duties: Leads discovery of insights from large datasets through research, using mathematical and/or statistical techniques for business application. Work with business partners and stakeholders to identify questions and build hypotheses, develop problem definition, analytical approach, and determine best approach to address business issues. Translate technical analyses and results into simple visuals and actionable items for business partners. Participate in the selection of research tools and technologies, design of a common research process and brainstorming new opportunities and methodologies. Build advanced algorithm and machine learning models using a variety of libraries/tools and cutting-edge techniques. Work with product and engineering teams to ensure that a model functions efficiently and delivers results that align with business objectives. Research and maintain awareness of industry best practices and business strategies. Bring new and innovative ideas and approaches to develop business solutions. Monitor industry and competitor trends to determine potential impact to predictive models. Identify, leverage, develop, in emerging technologies, open-source tools, and harnesses new techniques (e.g., GBM, Decision tree, Random Forest, NLP). Interact with leadership to assist in the development of strategic direction for the business or business partners. Lead research or analytics projects related to large, complex business initiatives. Apply knowledge of emerging trends and industry practices. Lead the development of new analytical and data science capabilities. Serve as an internal thought leader and provide knowledge transfer and training on new modelling tools and methodologies to less experienced staff. Identify opportunities for new machine learning solutions, exploring new data sources for enrichment, collecting appropriate labels for learning, establishing actionable metrics, and creating reusable model validations and risk mitigation. Provide advanced knowledge in predictive models such as parameterized methods, ensemble algorithms, deep neural network, and reinforcement learning algorithm. Execute assigned steps to support developing advanced models. Education Required: Bachelor or foreign equivalent in Computer Information Systems, Computer Science, Mathematics, Statistics, Data Science, Data Analytics or related field. Experience Required: 5 years of progressive experience as Data Scientist, Senior Analyst, Software Engineer or related occupation. Special Requirements: Must have at least 1 year of prior work experience in each of the following: Programming languages SQL, Spark, Python, R, and frameworks in the development, articulation, and implementation of coding practices for a team. Working with large datasets using big data technologies and script. Formulating, approaching, analysing, and solving analytical problems using a quantitative, scientific approach. Managing data to scale using data summarization, query and analysis software and tools. Developing and managing projects and effectively leading interdisciplinary teams to accomplish project goals. #LI-DNI PLEASE NOTE: Applicants must be legally authorized to work in the United States. At this time, we are not able to sponsor or assume sponsorship of employment visas. If you have a disability under the Americans with Disabilities Act or similar state or local law and you wish to discuss potential reasonable accommodations related to applying for employment with us, please contact our Benefits Department at ************. Notice to Recruitment Agencies: Resumes submitted for this or any other position without prior authorization from Human Resources will be considered unsolicited. BWS and / or its affiliates will not be responsible for any fees associated with unsolicited submissions. We are an Equal Opportunity Employer. We do not discriminate on the basis of age, ancestry, color, gender, gender expression, gender identity, genetic information, marital status, national origin or citizenship (including language use restrictions), denial of family and medical care leave, disability (mental and physical) , including HIV and AIDS, medical condition (including cancer and genetic characteristics), race, religious creed (including religious dress and grooming practices), sex (including pregnancy, child birth, breastfeeding, and medical conditions related to pregnancy, child birth or breastfeeding), sexual orientation, military or veteran status, or other status protected by laws or regulations in the locations where we operate. We do not tolerate discrimination or harassment based on any of these characteristics. The collection of your personal information is subject to our HR Privacy Notice Benefits and Compensation We offer a competitive compensation package, performance-based incentives, and a comprehensive benefits program-including health, dental, vision, 401(k) with company match, paid time off, and professional development opportunities.

Empower Your Future: At MetOx International, we're pioneering the next era of energy security and abundance through breakthrough superconducting technology. As a Senior Data Scientist, you'll join a dynamic team committed to strengthening the world's energy systems to make them more resilient, efficient, and reliable. Based at our global headquarters in Houston, TX, the Senior Data Scientist will lead advanced analytics, modeling, and machine learning efforts across our manufacturing operations. In this role, you will partner closely with R&D, process engineering, quality, and operations to translate complex process challenges into data-driven insights that improve yield, quality, and scalability. This is a highly technical, hands-on role for someone who thrives at the intersection of process engineering, applied mathematics, and industrial data science, and who is excited to drive measurable impact in advanced materials manufacturing. Key Responsibilities Process Analytics & Optimization Develops and deploys statistical models for process characterization, optimization, and quality control in superconductor manufacturing. Designs and executes design of experiments (DOE) to identify critical process parameters and optimize production outcomes. Implements statistical process control (SPC) methodologies including multivariate control charts and process capability analysis. Conducts root cause analysis using advanced statistical techniques combined with process engineering knowledge. Advanced Modeling & Machine Learning Builds physics-informed models that combine first-principles engineering with machine learning approaches. Develops predictive models for yield optimization, defect detection, and predictive maintenance. Applies time-series analysis and forecasting for process monitoring and anomaly detection. Implements computer vision and machine learning solutions for automated quality inspection. Mathematical Modeling & Simulation Applies advanced mathematical techniques including optimization theory, differential equations, and numerical methods to solve complex manufacturing challenges. Develops digital twins and process simulation models for scenario analysis and process improvement. Performs multivariate statistical analysis to understand complex interactions in manufacturing processes. Builds decision support tools using mathematical optimization for production planning and resource allocation. ⠀Data Infrastructure & Pipeline Development Designs and implements scalable data pipelines for real-time process monitoring across manufacturing operations. Integrates data from multiple sources including SCADA systems, MES platforms, databases, and sensor networks. Develops automated reporting systems for KPI tracking, process drift detection, and quality metrics. Establishes best practices for data governance, version control, and reproducible research. Technical Leadership & Collaboration Leads cross-functional data science projects involving R&D, process engineering, quality, and operations teams. Mentors junior data scientists and engineers on statistical methods, machine learning, and best practices. Translates complex process engineering challenges into tractable data science problems. Communicates analytical findings and recommendations to technical and executive stakeholders. Drives adoption of data-driven decision-making and advanced analytics across the organization. Other duties as assigned Minimum Qualifications: Bachelor's degree in Chemical Engineering, Materials Science, Applied Mathematics, Statistics, Data Science, or related technical field. 4 years of professional experience in data science or analytics within manufacturing, process engineering, or industrial R&D environments. Demonstrated experience in statistical process control, design of experiments, and process optimization. Preferred Qualifications: Master's or PhD in Chemical Engineering, Materials Science, Applied Mathematics, Statistics, or related field. Experience in process-intensive industries (semiconductor, chemical, pharmaceutical, or advanced materials manufacturing). Six Sigma Black Belt or equivalent process improvement certification. Experience with superconductor manufacturing, electrochemistry, thin-film deposition, or related materials processes. Publication record in process engineering, applied statistics, or machine learning. Experience with industrial automation systems (SCADA, MES, OPC, MQTT). Knowledge, Skills, & Abilities: Process Engineering & Domain Knowledge Deep understanding of manufacturing processes, unit operations, and process dynamics. Expertise in statistical process control (SPC), process capability analysis (Cp, Cpk), and control chart theory. Proficiency with design of experiments including factorial designs, response surface methodology, and Taguchi methods. Knowledge of quality management systems and continuous improvement methodologies. Strong foundation in mathematical modeling and advanced statistical methods Expert knowledge of multivariate statistics, time-series analysis, hypothesis testing, and Bayesian inference. Strong foundation in linear algebra, calculus, differential equations, and optimization theory. Experience with dimensionality reduction techniques (PCA, PLS, factor analysis). Understanding of numerical methods and computational algorithms. Machine Learning & AI Advanced proficiency in machine learning techniques including regression, classification, ensemble methods, and neural networks. Experience with computer vision and deep learning frameworks (TensorFlow, PyTorch, YOLO, etc.). Knowledge of model validation, cross-validation, and hyperparameter optimization. Familiarity with MLOps practices for model deployment and monitoring. Technical Programming & Tools Expert-level programming in Python (NumPy, SciPy, Pandas, Scikit-learn, Matplotlib, Plotly). Proficiency with statistical analysis software (Minitab, JMP, or equivalent). Advanced SQL skills for complex data extraction and manipulation from manufacturing databases. Experience with version control (Git), containerization (Docker), and CI/CD practices. Familiarity with data visualization platforms (Grafana, Tableau, Power BI, Metabase). Soft Skills & Leadership Exceptional analytical and problem-solving abilities with attention to detail. Strong communication skills with ability to explain complex mathematical and statistical concepts to diverse audiences. Proven ability to lead projects and mentor team members. Self-motivated with ability to work independently and manage multiple priorities. Collaborative mindset with experience working across engineering, operations, and business functions. Strategic thinking with ability to connect data insights to business objectives. Physical Demands: This position requires sitting at a desk and viewing a computer screen for extended periods while working or performing other office tasks. Ability to move around the office, including occasional standing, walking, and bending to retrieve documents, attend meetings, or use office equipment. Some light lifting may be required, up to 20 lbs. MetOx is proud to offer competitive benefits including: Health, dental, and vision available on the first day of employment 401(k) match Paid parental leave & adoption assistance Educational reimbursement And more! We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law.

Cognite operates at the forefront of industrial digitalization, building AI and data solutions that solve some of the world's hardest, highest-impact problems. With unmatched industrial heritage and a comprehensive suite of AI capabilities, including low-code AI agents, Cognite accelerates the digital transformation to drive operational improvements. Our moonshot is bold: unlock $100B in customer value by 2035 and redefine how global industry works. What Cognite is Relentless to achieve We thrive in challenges. We challenge assumptions. We execute with speed and ownership. If you view obstacles as signals to step forward - not step back - you'll feel at home here. Join us in this venture where AI and data meet ingenuity, and together, we forge the path to a smarter, more connected industrial future. How you'll demonstrate Ownership The Senior Data Science team at Cognite plays a crucial role in building data-driven solutions that empower our clients to make impactful business decisions. As a Senior Data Scientist at Cognite, you will work on challenging data problems with leaders in the industry. You will be a part of cross-functional teams that include data engineers, solution architects, and project managers. Together, your focus will be on configuring, deploying, and operationalizing digital solutions in sectors such as Oil and Gas, Power & Utilities, and Manufacturing. Additionally, you will engage with clients and Subject Matter Experts (SMEs) to understand their desired outcomes, lead discovery workshops, and provide insights on potential strategies and obstacles, ensuring the technical solution aligns with industrial reality. The Data Science team is a part of the AMER delivery team in our Global Delivery organization. Global Delivery is truly global, with offices in Houston & Phoenix (USA), Tokyo (Japan), Oslo (Norway), and Bengaluru (India). We are a good mix of Project Managers, Senior Data Scientists, Data Engineers, and Solution Architects with deep domain expertise. We are responsible for delivering successful projects that are flexible and scalable, and foster adoption of our product. In sum, we derive valuable insights from previously hidden data, enabling workers and leaders to transform how heavy asset industries operate to become more efficient and sustainable. As a Senior Data Scientist you are responsible for the following, but not limited to: Develop and deploy scalable solutions for customer use cases from Oil and Gas, Manufacturing, and Power & Utilities industries using Cognite's core capabilities. Participate in intensive use case generation workshops with Subject Matter Experts (SMEs) to understand the problem, industry domain knowledge, and how it maps to the data. Perform data cleansing and exploratory data analysis. Implement physical models / machine learning models in Python and deploy to our model hosting environment. Design and develop domain-specific information and data models. Apply GenAI techniques to enhance data-driven decision-making in customer use cases. Develop robust front-end User Interfaces (UIs) and dashboards using Streamlit, Grafana, Power BI, Plotly or Dash. Experience with React for bespoke UI development is a plus. Leverage strong understanding of solution architecture to ensure deployed solutions are flexible, scalable, and fully integrated into the client's industrial landscape. Utilize and contribute to solution templates and best practices within the Data Science team. Mentoring and coaching junior team members is an important part of being a Senior at Cognite. Collaborate with data engineers, project managers, and solution architects on project deliveries to enable our customers to achieve the full potential of our industrial dataops platform. Support customers and partners in conducting data science tasks with Cognite products. The Impact you bring to Cognite We believe most of these should match your experience: Bachelor/Master of Science in a quantitative field or mechanical, systems, electrical, or industrial engineering. 5+ years of full-time work experience as a Senior Data Scientist (preferably within related industry), or Senior Data Scientist with domain expertise in Oil and Gas or Manufacturing. Proficient experience with Python and SQL. Experience with Python in a production setting is a plus. Experience with machine learning methods and techniques, statistics and/or optimization as well as physics based modeling. Experience with Git. Experience working customer-faced, with external customers. Front-end development experience with frameworks such as React or native knowledge of UI platforms like Streamlit/Dash is highly desired. Understanding of solution architecture, system design, and deployment best practices in a cloud environment. Experience with managed cloud services such as GCP, Azure or AWS is a plus. Strong domain knowledge or a good understanding of Industry and Asset Performance Management-covering areas like production optimization-is a big plus. (As key CDF advisors, we want our Senior Data Scientists to have a good understanding of our customer data, and assist them in understanding how CDF can help solve their problems related to production optimization). Enjoy working in cross-functional teams. Able to deliver independently, coach and mentor others internally. Enjoy challenges and dare to set ambitious goals that drive innovation. Humility to ask for help and enjoy sharing knowledge with others. Equal Opportunity Cognite is committed to creating a diverse and inclusive environment at work and is proud to be an equal opportunity employer. All qualified applicants will receive the same level of consideration for employment.

Job Description Cognite operates at the forefront of industrial digitalization, building AI and data solutions that solve some of the world's hardest, highest-impact problems. With unmatched industrial heritage and a comprehensive suite of AI capabilities, including low-code AI agents, Cognite accelerates the digital transformation to drive operational improvements. Our moonshot is bold: unlock $100B in customer value by 2035 and redefine how global industry works. What Cognite is Relentless to achieve We thrive in challenges. We challenge assumptions. We execute with speed and ownership. If you view obstacles as signals to step forward - not step back - you'll feel at home here. Join us in this venture where AI and data meet ingenuity, and together, we forge the path to a smarter, more connected industrial future. How you'll demonstrate Ownership The Senior Data Science team at Cognite plays a crucial role in building data-driven solutions that empower our clients to make impactful business decisions. As a Senior Data Scientist at Cognite, you will work on challenging data problems with leaders in the industry. You will be a part of cross-functional teams that include data engineers, solution architects, and project managers. Together, your focus will be on configuring, deploying, and operationalizing digital solutions in sectors such as Oil and Gas, Power & Utilities, and Manufacturing. Additionally, you will engage with clients and Subject Matter Experts (SMEs) to understand their desired outcomes, lead discovery workshops, and provide insights on potential strategies and obstacles, ensuring the technical solution aligns with industrial reality. The Data Science team is a part of the AMER delivery team in our Global Delivery organization. Global Delivery is truly global, with offices in Houston & Phoenix (USA), Tokyo (Japan), Oslo (Norway), and Bengaluru (India). We are a good mix of Project Managers, Senior Data Scientists, Data Engineers, and Solution Architects with deep domain expertise. We are responsible for delivering successful projects that are flexible and scalable, and foster adoption of our product. In sum, we derive valuable insights from previously hidden data, enabling workers and leaders to transform how heavy asset industries operate to become more efficient and sustainable. As a Senior Data Scientist you are responsible for the following, but not limited to: Develop and deploy scalable solutions for customer use cases from Oil and Gas, Manufacturing, and Power & Utilities industries using Cognite's core capabilities. Participate in intensive use case generation workshops with Subject Matter Experts (SMEs) to understand the problem, industry domain knowledge, and how it maps to the data. Perform data cleansing and exploratory data analysis. Implement physical models / machine learning models in Python and deploy to our model hosting environment. Design and develop domain-specific information and data models. Apply GenAI techniques to enhance data-driven decision-making in customer use cases. Develop robust front-end User Interfaces (UIs) and dashboards using Streamlit, Grafana, Power BI, Plotly or Dash. Experience with React for bespoke UI development is a plus. Leverage strong understanding of solution architecture to ensure deployed solutions are flexible, scalable, and fully integrated into the client's industrial landscape. Utilize and contribute to solution templates and best practices within the Data Science team. Mentoring and coaching junior team members is an important part of being a Senior at Cognite. Collaborate with data engineers, project managers, and solution architects on project deliveries to enable our customers to achieve the full potential of our industrial dataops platform. Support customers and partners in conducting data science tasks with Cognite products. The Impact you bring to Cognite We believe most of these should match your experience: Bachelor/Master of Science in a quantitative field or mechanical, systems, electrical, or industrial engineering. 5+ years of full-time work experience as a Senior Data Scientist (preferably within related industry), or Senior Data Scientist with domain expertise in Oil and Gas or Manufacturing. Proficient experience with Python and SQL. Experience with Python in a production setting is a plus. Experience with machine learning methods and techniques, statistics and/or optimization as well as physics based modeling. Experience with Git. Experience working customer-faced, with external customers. Front-end development experience with frameworks such as React or native knowledge of UI platforms like Streamlit/Dash is highly desired. Understanding of solution architecture, system design, and deployment best practices in a cloud environment. Experience with managed cloud services such as GCP, Azure or AWS is a plus. Strong domain knowledge or a good understanding of Industry and Asset Performance Management-covering areas like production optimization-is a big plus. (As key CDF advisors, we want our Senior Data Scientists to have a good understanding of our customer data, and assist them in understanding how CDF can help solve their problems related to production optimization). Enjoy working in cross-functional teams. Able to deliver independently, coach and mentor others internally. Enjoy challenges and dare to set ambitious goals that drive innovation. Humility to ask for help and enjoy sharing knowledge with others. Equal Opportunity Cognite is committed to creating a diverse and inclusive environment at work and is proud to be an equal opportunity employer. All qualified applicants will receive the same level of consideration for employment.

The Senior Data Scientist II analyzes complex structured and unstructured data using state-of-the-art data science methods for data driven decision making. Develop algorithms that enable machines to perform tasks that typically require human intelligence. Moreover, this role uses both knowledge of data science and Artificial Intelligence methods and applies them to solve real world problems. The Senior Data Scientist II mentors junior team members, leads development of data products, communicates complex solutions effectively, and guides decision-making within the organization. What You Will Do: * Apply advanced data science concepts to deliver data-driven digital offerings and insights using Databricks Lakehouse architecture. * Utilize modern machine learning methods and domain understanding to support the creation of new products and services, leveraging MLflow for experiment tracking and model lifecycle management. * Collaborate with data and analytics teams and cross-functional departments such as digital, services, class, and engineering to build scalable ML solutions and deliver actionable insights. * Write independent source code in Python, PySpark, and SQL, validate and test models, and use Databricks Feature Store for consistent feature reuse and governance. * Design and implement robust data architectures using Delta Lake and manage data assets securely via Unity Catalog and Azure Data Lake. * Combine Agile methodologies with data science practices to build advanced analytics and AI products using Databricks Workflows and Azure ML Pipelines. * Develop, test, deploy, and maintain machine learning and AI models using Databricks Runtime for ML, ensuring scalability, performance, and governance. * Lead the data-driven decision-making process, from data collection and analysis to implementation and monitoring of solutions using Databricks Jobs, CI/CD pipelines, and Azure DevOps. * Support organizational decision-making based on the results of analytics efforts, ensuring traceability and governance via Unity Catalog and Azure Purview. * Work independently on data engineering, preprocessing, and preparation tasks using Databricks Notebooks, SQL Warehouses, and Azure Synapse Analytics. * Mentor data scientists, ASPIRES, and interns, providing guidance and support in their professional development and technical growth. * Evaluate and partner with external customers, vendors, university relations, and other teams to drive innovation and collaboration. * Stay current in the field of AI and advanced analytics, with a focus on innovations within the Databricks, Azure, and OpenAI ecosystems, including LLMs, GenAI, and MLOps. * Develop and deploy scalable and interpretable data products per business-defined requirements using Databricks Repos, Model Serving, and Azure Machine Learning. What You Will Need: Education and Experience * Bachelor's Degree in Data Science, Information Systems, Computer Science, Engineering or other relevant field with relevant experience. * Required -5 or more years of experience in Data Science, Information Systems, Computer Science, Engineering, or other field with relevant experience. * Preferred - Master's Degree in Data Science, Data Analytics, Information Systems, Computer Science, Engineering or other relevant field. Preferred - 1 or more years of work experience as a Sr Data Scientist, demonstrating leadership on projects involving applied AI and Machine Learning Knowledge, Skills, and Abilities * Strong written and verbal communications skills * Strong written and verbal communication skills, with the ability to translate complex data into actionable insights. * Experienced in working with cross-functional teams to understand business challenges and deliver data-driven solutions. * Proficient in machine learning, data mining, statistical analysis, and applied AI methods using Databricks, Azure ML, and Dataiku. * Skilled in developing scalable ML solutions and translating analytics into business impact. * Advanced proficiency in Python, PySpark, SQL, and tools such as Jupyter, VS Code, and MLflow. * Experience with database technologies and architectures including Delta Lake, Azure Data Lake, SQL Warehouses, and Synapse Analytics. * Hands-on experience with AutoML platforms such as Dataiku, and familiarity with Azure AutoML. * Deep understanding of Azure Cloud resources, including Azure Machine Learning, Azure DevOps, Azure Cognitive Search, and Azure OpenAI. * Familiarity with Generative AI solutions, Large Language Models, and NLP frameworks like Hugging Face Transformers. * Ability to develop a working knowledge of ABS Rules, Guides, statutory regulations, and related instructions, as well as the ABS Employee Safety Policy. It Would Be Nice If You Have: * Career Essentials in Generative AI by Microsoft and LinkedIn * Build Your Generative AI Productivity Skills with Microsoft and LinkedIn * Azure AI Fundamentals * Azure Data Scientist Associate * Azure AI Engineer Associate/Databricks Certification Reporting Relationships: Reports to Senior Manager on Data and Analytics team Notice: This position requires access to information that is subject to control by the Export Administration Regulations and/or the International Traffic in Arms Regulations. Any offer of employment shall be contingent upon the Company's verification that the candidate is a "U.S. Person" or upon the receipt of all necessary export licenses or authorizations that may be required by U.S. export control laws. "U.S. Persons" are defined as U.S. citizens, U.S. lawful permanent residents (i.e., "green card" holders), or any individual granted protected status under the Immigration and Nationality Act (8 U.S.C. § 1324b(a)(3)), including asylees and refugees. In the event a candidate refuses or cannot otherwise provide the necessary information for the Company to determine whether such licenses may be required, or for the Company to obtain any required licenses, the Company shall maintain the exclusive right to discontinue the application process and/or withdraw any contingent offer that has been made.

Company Information: Linqx is an industry-leading provider of end-to-end digital solutions and analytics for the oil and gas sector, leveraging advanced data analytics to optimize engineering and operations​. Its cloud-based platforms deliver AI-driven insights that enhance reservoir performance and streamline workflows​​. Driven by a mission of data-driven innovation​, Linqx combines cutting-edge technology with oilfield expertise to deliver transformative results​. Position Summary: Seeking an experienced and highly skilled Data Scientist to join our dynamic team. The ideal candidate will possess a strong foundation in data science, machine learning, and data engineering, with a particular focus on developing and deploying cutting-edge generative AI models. Incumbents will work closely with cross-functional teams to drive impactful data-driven decisions and innovations across the organization. Our dynamic approach to technology offers an exciting environment for this role that's focused on big data, machine learning, and advanced analytics. Key Roles / Responsibilities: Design, implement, and deploy advanced machine learning models and algorithms, particularly in Generative AI (e.g., GANs, transformers, diffusion models). Leverage deep learning frameworks (such as TensorFlow, PyTorch, or JAX) to build and train state-of-the-art models for natural language processing (NLP), computer vision (CV), and other generative tasks. Collaborate with engineering teams to ensure seamless integration of AI/ML solutions into production environments, optimizing for performance and scalability. Work with technology and business leaders to evolve data-driven vision, communication channels, and all supporting documentation Utilize advanced statistical techniques and data modeling methods to analyze large, complex datasets and provide actionable insights. Develop data pipelines for cleaning, processing, and transforming raw data into structured formats suitable for machine learning applications (i.e. familiarity with Lakehouse deployment/governance on Medallion architecture). Design, build, and maintain efficient and scalable data architectures and data storage solutions. Work on end-to-end machine learning workflows, including data preprocessing, feature engineering, model training, evaluation, and deployment. Continuously evaluate and optimize model performance and contribute to improving the overall AI/ML infrastructure and processes. Mentor and/or manage junior data scientists and engineers, fostering a culture of collaboration and continuous learning. Stay updated on the latest advancements in AI/ML research and apply innovative techniques to solve business problems. Document and communicate findings and solutions clearly to both technical and non-technical stakeholders. Participate and potentially drive data-specific technology selection activities Required Education, Experience, and Qualifications: Master's or PhD in Computer Science, Data Science, Engineering, or a related field, with a focus on machine learning, AI, or data engineering. Proven expertise in Generative AI, including experience with techniques such as GANs, VAEs, transformers, RAGs, and other advanced AI and deep learning models. Strong proficiency in programming languages like Python, R, or Julia, and hands-on experience with AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn, etc.). Extensive experience with data engineering, including data wrangling, ETL processes, data storage, and real-time data processing. In-depth knowledge of machine learning algorithms, deep learning, and statistical modeling techniques. Familiarity with cloud platforms (AWS, GCP, or Azure) and distributed computing frameworks (e.g., Spark, Hadoop). Experience in designing and optimizing data architectures for both batch and real-time data flows. Proficient with database systems (SQL, NoSQL) and data query languages. Strong problem-solving, analytical, and critical-thinking skills with the ability to work independently or as part of a team. Excellent communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences. Preferred Skills: Knowledge of NLP and CV applications, including experience with large-scale pre-trained models like GPT, BERT, or DALL·E. Expertise in model deployment and monitoring in production environments (e.g., Docker, Kubernetes, MLflow). Experience with version control systems (e.g., Git) and software development best practices. Familiarity with DevOps practices and CI/CD pipelines for machine learning projects. Published research in top-tier conferences or journals related to AI/ML or Generative AI. Benefits: Competitive Compensation Package Medical + Dental + Vision Coverage 401K + Company Match Life Insurance + Long Term Disability Coverage - 100% Company Paid Health Savings Account (HSA) Gym Reimbursement Program Tuition Reimbursement Program Wellness Check Program - Insurance Premium Discounts EAP Resources Paid Holidays Paid Time Off (PTO) Working Conditions: Year-round on-site in-office expectation (standard 5-day work week) Working with globally distributed team members and partners Prolonged periods sitting at a desk and working on a computer. Must be able to lift 15 pounds at times. Positions self to install equipment, including under desks. Moves throughout the building to access files. Must be able to comprehend and follow written and oral instructions. Must be able to complete tasks even with frequent interruptions. Must be able to use discretion and independent judgment as needed. Must be able to speak clearly on the phone and to fellow workers. This job description should not be interpreted as an exhaustive list of responsibilities or as an employment agreement between the employer and the employee. The above statements are intended to describe the general nature and level of work being performed by employees assigned to this classification and are subject to change as the needs of the employer and requirements of the job change. Any essential functions of this position will be evaluated as necessary should an employee/applicant be unable to perform the functions or requirements due to a disability as defined by the Americans with Disabilities Act (ADA). Reasonable accommodation for the specific disability will be made for the employee/applicant when possible. I acknowledge that I have read and understand the description of this position and have had the opportunity to ask my supervisor about any points I did not understand. I hereby state that I can perform the essential functions of this position with or without reasonable accommodation.

Job Description Daikin Comfort Technologies Mfg is seeking a professional, skilled individual for our Data Scientist position at our Waller, TX facility. The Data Scientist role at its core links business strategy to the data. The Data Scientist role at its core links business strategy to the data. He/she will transform structured or unstructured data into actionable information and predictive models to make a big impact across the organization. This individual will break down the hairiest of problems by applying the full data science toolkit and provide insights to stakeholders across the organization to change minds and hearts. He/she will keep the customer front of mind in all of the work and optimize the customer experience, which will translate to creating long-term business value. As a pioneering Data Scientist at Daikin, he/she will influence the cultural change around how we use, talk about, and ultimately value our data assets, as part of a broader Digital Transformation. Why work with us? > Benefits are effective on day one for all full-time direct hires. > Training programs are available to help guide team members and develop new skills. > Growth Opportunities - there are immense opportunities to grow your career. > You will be part of a Global Company - our family brands are backed by Daikin Industries, Ltd. Position Responsibilities may include: Gather, process, clean, enrich, and integrate structured and unstructured data to build advanced models to turn data into insights; creatively analyze data to understand drivers of historical business performance and build predictive models to inform future business strategies Deep understanding of our organization's data structure; look for ways to improve to enhance our ability to perform robust data analysis; create new data sets when there is little or no data available, to inform marketing analysis Engage with third-party data providers to strengthen and enrich data models as needed; inform purchase of net new data Deeply understand all sources of data across the enterprise, link to data strategy, and continually evolve ability to measure and track key data points to enable data-driven decisions Collect and provide quantitative and qualitative information to measure effectiveness of marketing activities and answer strategic business questions Analyze and discern campaign execution, targeting and optimization of marketing investment to deliver sales and operating profit across brands Utilize visualization solutions to improve timeliness of data delivery and provide better visibility to decision makers to help them monitor, measure, or predict how the company is performing Perform marketing research & analysis to inform customer targeting & segmentation, in addition to longitudinal tracking of Customer Lifetime Value across the enterprise Assist with internal assessments of workflow processes to identify inefficiencies, especially those where Marketing is involved, and propose more efficient processes and procedures via process automation leveraging tech platforms Assist with maintenance and management of Marketing SQL database and Snowflake cloud data warehouse Provide data science support and ad hoc analysis to enterprise leadership as needed Perform additional projects/duties to support ongoing business needs. Nature & Scope: Applies practical knowledge of job area typically obtained through advanced education and work experience Encouraged to seek continuous improvements Performs a range of mainly straightforward assignments Works independently with general supervision Problems faced are difficult but not typically complex Knowledge & Skills: Strong analytical skills with attention to detail; strong knowledge of statistical analysis, machine learning process, computer science principles, and basic programming principles Moderate data storytelling ability - ability to produce actionable information/insights, not just data crunching Strong communication skills, both verbally and written, capable of communicating with people of many different levels of an organization Knowledge of experimentation and testing of Minimum Viable Products to determine if proposed business models / solutions scale up Proficient in MS Office especially Excel; ability to translate data insights into PowerPoint presentations Strong understanding of relational databases with experience in SQL - Microsoft SQL Server, Oracle, Postgres Moderate experience with A/B testing and data science techniques to build and implement predictive models Strong experience with visualization tools such as Tableau, Qlik, or Microsoft Power BI (or similar applications) Moderate experience with Python, R, Alteryx or other analytics platforms a plus (or similar applications) Eager to make a big impact at a large company - you show up for work and get things done Natural ability and desire to work on a team - goes the extra mile when needed; ability to work independently too Ability to grasp complex concepts and systems quickly Ability to manage multiple projects and shift direction quickly Intellectual curiosity and strong passion for using data to solve problems creatively Ability to apply good judgment, strong work ethic, and integrity on the job. Experience: 3-5 years of work experience in a Marketing / Consulting / Business Analyst / Data Science role Experience solving complex business problems involving a heavy amount of analytics / data science Marketing-based experience preferred, but not required (either D2C or B2B performance marketing) HVAC industry experience preferred, but not required Education/Certification: Bachelor's degree (required) in Marketing / Business / Engineering / Statistics / Mathematics / Economics / Computer Science; or other related degree with strong quantitative emphasis Master's degree (preferred) in Data Science / Business Administration / Marketing People Management: No Physical Requirements / Work Environment: Must be able to perform essential responsibilities with or without reasonable accommodations Reports To: Qualified Applicants must be legally authorized for employment in the United States. Qualified applicants will not require employer sponsored work authorization now or in the future for employment in the United States. The Company provides equal employment opportunity to all employees and applicants regardless of a person's race, color, religion (including religious dress or grooming practices), creed, national origin (including language use restrictions), citizenship, uniform service member or veteran status, ancestry, disability, physical or mental disability (including HIV/AIDS), medical condition (including cancer and genetic characteristics), genetic information, request for protected leave, marital status, sex, pregnancy, age (over 40), sexual orientation, gender, gender identity or expression, political affiliation, or any other characteristic protected by law. The Company will comply with all federal and state regulations and statutes pertaining to individuals with disabilities.

Role: Data Scientist Role : 6 months Job Details: Must Have Skills (Top 2 technical skills only) Minimum 8 years of relevant experience in applying data mining, artificial intelligence, signal processing, machine learning, optimization etc. in business analytics or scientific/engineering settings Experience with statistical software, scripting languages, tools, and platforms (e.g., R, Python, Hadoop etc.) Nice to have skills (Top 2 only) A demonstrated ability to solve challenging business problems using a data science approach by developing novel and/or adapting existing computational methods Strong skills in communicating and presenting data-derived insights to non-technical audiences appropriately. Additional Information Thanks & Regards Praveen K. Paila ************

This role is a software- and data engineering-focused position responsible for turning real-world user needs into production-ready data pipelines, backend services, and data-driven applications. The primary focus is on data processing, system integration, performance, and reliability, working closely with business and operational users to continuously improve systems and dashboards so that data can be accurately and effectively used in real operational scenarios. This role emphasizes building and operating reliable data systems rather than research-oriented modeling or algorithm development. Key Responsibilities ●Work closely with internal users (e.g., operations, manufacturing, or business teams) to understand real usage scenarios and translate requirements into system designs, data pipelines, and reporting specifications ●Design, build, and maintain reliable data pipelines (ETL) using SQL and Python ●Develop and maintain backend services and APIs to support data access, system integration, and application functionality ●Build and enhance BI dashboards and visualizations (e.g., Tableau) with a strong focus on data accuracy, usability, and real-world adoption ●Collaborate with engineers, IT teams, and cross-functional partners on system integration and workflow optimization ●Optimize system performance and architecture as data volume and usage patterns evolve ●Proactively monitor data quality and system reliability, identifying and resolving issues that impact user experience ●Collaborate with global engineering and data teams, including partners in Asia, to align on system design, data workflows, and implementation details. This role values production-ready systems that are stable, accurate, and actually used, rather than model-centric or research-driven solutions. Qualifications Must Have ●Hands-on experience with data processing, cleaning, and transformation, turning raw data into structured and usable datasets ●Proficiency in Python, SQL, and Git, with experience applying them in real projects ●Strong SQL skills; experience participating in or being familiar with database schema design, with an understanding of how data models support usage scenarios ●Backend development experience; experience participating in or being familiar with building APIs in Python to support system integration and data access ●Experience working with cross-functional teams and the ability to clearly explain technical solutions and trade-offs ●Experience collaborating with users to translate real-world requirements into deployable systems, data workflows, or dashboards Nice to Have ●Experience with Linux and Docker, including system deployment or operations ●Familiarity with CI/CD pipelines ●Experience with database performance tuning or large-scale data processing ●Ability to communicate in Spanish or Chinese for work-related discussions ●Comfortable working in a global, cross-time-zone collaboration environment

Job Title: Data Scientist Department: Purchasing Reports To: COO Location: 6969 North Fwy, Houston, TX 77076 Employment Type: Full-time We are seeking a highly skilled and analytical Data Scientist to join our Purchasing Department. The successful candidate will leverage data analytics, machine learning, and statistical modeling to optimize procurement processes, forecast demand, and enhance supply chain efficiency. This role requires strong data management skills and collaboration with cross-functional teams to drive data-driven decision-making and cost reduction initiatives. Key Responsibilities: Data Analysis & Reporting: Develop predictive models to forecast demand, optimize inventory levels, and reduce procurement costs. Analyze historical purchasing data to identify trends, inefficiencies, and opportunities for cost savings. Build and maintain data pipelines and dashboards to monitor supplier performance, lead times, and pricing trends. Generate actionable insights and reports for senior management to support strategic decision-making. Machine Learning & Process Optimization: Implement machine learning algorithms to enhance supplier selection and risk assessment. Work with procurement teams to develop data-driven negotiation strategies and supplier recommendations. Automate data collection, cleaning, and reporting processes for improved efficiency. Utilize statistical analysis to assess market trends, raw material costs, and external factors affecting purchasing decisions. Collaboration & System Integration: Work closely with IT and supply chain teams to integrate data solutions with existing ERP and procurement systems. Support cross-functional teams including procurement, inventory management, and supplier relations to ensure smooth data utilization. Qualifications: Education & Experience: Bachelor's degree in Data Science, Statistics, Computer Science, Supply Chain Management, or a related field. At least 2-4 years of experience in data analysis, machine learning, or procurement analytics. Proven experience in data modeling, with strong expertise in statistical analysis and predictive analytics. Skills & Competencies: Proficiency in programming languages such as Python, R, or SQL for data manipulation and analysis. Experience with data visualization tools (e.g., Tableau, Power BI) to present insights effectively. Strong problem-solving and critical-thinking abilities. Excellent communication and interpersonal skills for cross-functional collaboration. Detail-oriented with strong organizational skills and the ability to manage multiple priorities. Preferred: Experience with ERP systems (e.g., SAP, Oracle) and procurement analytics tools. Knowledge of machine learning frameworks and process improvement methodologies (e.g., Lean, Six Sigma). Job Details: Work Schedule: Mon-Fri: 8:00 AM - 5:30 PM Sat: 8:00 AM - 3:00 PM Employee Benefits: Health Benefits: Medical, Vision, and dental coverage (details provided after the initial period). 401k: Eligibility after six months. Vacation Time: 40 hours per year, accrued on a pro-rata basis. Sick Time: 40 hours per year, accrued on a pro-rata basis. Additional Benefits: Employee discounts PAYACTIV Paid Holidays (6 days): New Year's Day Memorial Day Independence Day Labor Day Thanksgiving Day Christmas Day

Job Responsibilities Principal Accountabilities Leads high priority projects that impact the organization. Leads complex issues and problems, and refers more complex issues to higher-level staff. Provides technical supervision/mentoring to other data scientists and trains the broader audience on data science developments. Provides leadership, coaching, and/or mentoring to subordinate group. Develops custom data models and algorithms to apply to data sets. Develops and applies algorithms or models to key business metrics with the goal of improving operations or answering business questions. Provides findings and analysis for use in decision making. Performs research, analysis, and modeling on organizational data. Maintains existing models and evaluates their goodness of fit. Provides in-depth data insights from structured and unstructured data for complex business problems through use of advanced analytics techniques, predictive modeling, data mining/visualization and pattern analysis tools. Develops and tests hypotheses and communicates findings in clear, precise and actionable manner to project and leadership teams. Works closely with teams to identify, understand, and resolve data issues and improve efficiency, productivity and scalability of data processes. Assists with the evaluation of data science vendors and tools. Ensures safe care to patients, staff and visitors; adheres to all policies, procedures, and standards within budgetary specifications including time management, supply management, productivity and quality of service. Promotes individual professional growth and development by meeting requirements for mandatory/continuing education and skills competency; supports department-based goals which contribute to the success of the organization; serves as preceptor, mentor and resource to less experienced staff. Demonstrates commitment to caring for every member of our community by creating compassionate and personalized experiences. Models service standards by providing safe, caring, personalized and efficient experiences to patients and colleagues. Other duties as assigned. Minimum Qualifications Education Bachelors Degree in science, engineering, computer science, mathematics, statistics, or related STEM field required. Masters Degree in Data Science preferred. Licenses/Certifications: (None) Experience / Knowledge / Skills Seven (7) years of experience in data science is required Professional experience in hospital setting, medical informatics, healthcare information technology/finance/revenue cycle data management, or Electronic Health Record (EHR) data management is preferred Business analytical skills (process flows, procedures, spreadsheets, modeling, etc.), technical expertise, mathematical skills and good understanding of design and architecture principles are required Possesses deep understanding of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks Proficient understanding of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications Ability to communicate, gather requirements and execute storytelling with data Possesses advanced level knowledge of the data science project life cycle Proficient programming skills in addition to a working knowledge and experience of statistical analysis tools Demonstrates proficiency in problem solving, analytical reasoning and decision-making skills Demonstrates proficiency in identifying and seeking needed information to perform problem/situation analysis Advanced level of understanding and experience in researching and resolving data issues with a logical, instinctive, and problem-solving mentality working with large, complex and incomplete sources Exhibits strong project management skills, with an ability to work independently on multiple projects with competing priorities and a strong commitment to meeting goals and deadlines Advanced understanding of SQL database management tools Exceptional analytical skills and ability to understand and interpret results based on advanced statistical techniques Strong written and verbal communication skills in IT and business environments; ability to communicate to technical and non-technical audiences Ability to work under minimal supervision in a fast-paced multidisciplinary environment Advanced knowledge of data science methods time series forecasting, linear regression, A/B testing, statistical testing, Clustering, etc. Superior customer service in the form of first-rate work products and project management Strong ability to manage challenging client situations Strong ability to troubleshoot and recommend solutions Strong ability to translate complex information for a wide range of stakeholders Benefits Dental Insurance, Medical Insurance, Vision Insurance, Life Insurance, Retirement, Equity, PTO,

VERY URGENT AND IMMEDIATE NEED. Note: Need Only US Citizen, Green Card, EAD-GC, J2 EAD, H4 EAD, L2 EAD, and TN Visa. Job Title: Data Scientist Duration: 06+ Months Contract Note: Oil, Gas and energy background in Preferred Job Description: You will work with a team of data engineers and scientists who use data and apply cutting statistical machine learning models to build forecasting models for different energy markets. The entire Data team works collaboratively and is a strong partner for teams across the company. You will get to meet and learn from diverse and talented colleagues. Specific responsibilities include: Analyze energy time series and summarize the statistical properties of energy signals Build predictive models and forecast signals for day-ahead consumption data Evaluate the performance and compare the results with existing models Deploy the best model and document the result of this research Business Skills Excellent verbal, written, and interpersonal communication skills Strong understanding of the product development lifecycles Strong understanding of software development, testing and integration methodologies Personal effectiveness/credibility Strong problem solving and analysis skills Technical Skills Proficiency with Python or R, SQL and familiarity with working in big data environments (2 years minimum) At least 2+ years of experience of deploying machine learning models and frameworks in production At least 3 years of experience with: Experiences in both Supervised and Unsupervised machine learning models (Regressions, Gradient Boosted methods, SVMs, Random Forests, Clustering) Familiar with python packages such as Pandas, SkLearn, Numpy etc Deep learning (CNN, RNN, LSTM) and framework library (e.g., Keras, TensorFlow, PyTorch) and Graph Neural Networks Evaluation and hypothesis testing. At least 3 years of experience with Cloud computing platforms such as AWS, Azure (preferably AWS) Standard concepts and technologies used in CI/CD build and deployment pipelines. At least 2 years of experience in distributed computing frameworks such as Spark or Pyspark is desirable.

DPR Construction is seeking a skilled Senior Data Scientist to help advance our data-driven approach to building. In this role, you'll use statistical analysis, machine learning, and data visualization to turn complex construction and business data into actionable insights that improve project planning, cost forecasting, resource management, and safety. Working with project and operations teams, you'll build and deploy scalable, secure data solutions on cloud platforms like Azure and AWS, driving innovation and operational excellence across DPR's projects. Responsibilities * Data analysis and modeling: Analyze large datasets to identify trends, bottlenecks, and areas for improvement in operational performance. Build predictive and statistical models to forecast demand, capacity, and potential issues. * Develop and deploy models: Build, test, and deploy machine learning and AI models to improve operational processes. * Analyze operational data: Examine data related to projects, production, supply chains, inventory, and quality control to identify patterns, trends, and inefficiencies. * Optimize processes: Use data-driven insights to streamline workflows, allocate resources more effectively, and improve overall performance. * Forecast and predict: Create predictive models to forecast outcomes, such as demand, and inform strategic decisions. * Communicate findings: Present findings and recommendations to stakeholders through reports, visualizations, and presentations. * Ensure reliability: Build and maintain reliable, scalable, and efficient data science systems and processes. * Collaboration: Partner with project managers, engineers, and business leaders to ensure data solutions are aligned with organizational goals and deliver tangible improvements. * Continuous Learning: Stay current with advancements in data science and machine learning to continually enhance the company's data capabilities. * Reporting and communication: Create dashboards and reports that clearly communicate performance trends and key insights to leadership and other stakeholders. Translate complex data into actionable recommendations. * Performance monitoring: Implement data quality checks and monitor the performance of models and automated systems, creating feedback loops for continuous improvement. * Experimentation: Design and evaluate experiments to quantify the impact of new systems and changes on operational outcomes. Qualifications * Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Engineering, or a related field. * 7+ years of experience in data science roles within AEC, product or technology organizations. * At least 4 years of experience working with cloud platforms, specifically Azure and AWS, for model deployment and data management. * Strong proficiency in Python or R for data analysis, modeling, and machine learning, with experience in relevant libraries (e.g., Scikit-learn, TensorFlow, PyTorch) and NLP frameworks (e.g., GPT, Hugging Face Transformers). * Expertise in SQL for data querying and manipulation, and experience with data visualization tools (e.g., Power BI, Tableau). * Solid understanding of statistical methods, predictive modeling, and optimization techniques. * Expertise in statistics and causal inference, applied in both experimentation and observational causal inference studies. * Proven experience designing and interpreting experiments and making statistically sound recommendations. * Strategic and impact-driven mindset, capable of translating complex business problems into actionable frameworks. * Ability to build relationships with diverse stakeholders and cultivate strong partnerships. * Strong communication skills, including the ability to bridge technical and non-technical stakeholders and collaborate across various functions to ensure business impact. * Ability to operate effectively in a fast-moving, ambiguous environment with limited structure. * Experience working with construction-related data or similar industries (e.g., engineering, manufacturing) is a plus. Preferred Skills * Familiarity with construction management software (e.g., ACC, Procore, BIM tools) and knowledge of project management methodologies. * Hands-on experience with Generative AI tools and libraries. * Background in experimentation infrastructure or human-AI interaction systems. * Knowledge of time-series analysis, anomaly detection, and risk modeling specific to construction environments. DPR Construction is a forward-thinking, self-performing general contractor specializing in technically complex and sustainable projects for the advanced technology, life sciences, healthcare, higher education and commercial markets. Founded in 1990, DPR is a great story of entrepreneurial success as a private, employee-owned company that has grown into a multi-billion-dollar family of companies with offices around the world. Working at DPR, you'll have the chance to try new things, explore unique paths and shape your future. Here, we build opportunity together-by harnessing our talents, enabling curiosity and pursuing our collective ambition to make the best ideas happen. We are proud to be recognized as a great place to work by our talented teammates and leading news organizations like U.S. News and World Report, Forbes, Fast Company and Newsweek. Explore our open opportunities at ********************

Welcome to epicenter of personal power. We re driven by the idea of a smarter, cleaner, digitally-enhanced energy ecosystem and the possibilities that brings to the world and to the seven million customers we serve. Consumer s data scientists use a combination of technical and business skills to help brands achieve their financial and strategic objectives. A Data Scientist learns the job while performing hands-on analytics and modeling. Essential Duties/Responsibilities: Adhere to our culture of humility, curiosity, and impact Process data using Python, PySpark, and Databricks Develop models and dashboards Learn the job while performing hands-on analytics and modeling Help business partners make more profitable decisions based on customer and prospect insights Minimum Requirements: 0-3 years of experience in data analysis or related field Master s degree in a quantitative discipline or equivalent practical experience Experience with statistical software and database languages Preferred Qualifications: Experience using data science to improve customer experience and business profitability PhD in a quantitative discipline Proficiency in Python packages such as PySpark, NumPy, pandas, scikit-learn, XGBoost, Matplotlib, and lifelines Theoretical and practical knowledge of methods such as frequentist statistics, Bayesian statistics, forecasting, optimization, causal inference, machine learning, and natural language processing Proficiency with version control Experience with reading and writing data in the cloud Ability to collaborate effectively with teammates across functions with strong skills in persuasive and informative speaking