Senior data scientist jobs in League City, TX - 217 jobs

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-TW1

*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.

Job Description 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.

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.

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.

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 ************

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

Clearance: DHS Suitability - nice to have US Citizenship is required Experience: 5+ years Remote/Hybrid/Onsite: 100% Onsite work (non-negotiable) Skill Level Desired Years Exp Senior 5-10 Expert 11-15 Subject Matter Expert 16+ Full Time: Direct Hire No 3rd Party Vendors - No exceptions Note: Available Immediately & Benefits posted below Introduction Our client seeks a skilled Data Scientist / Data Engineer to join our team and support the Houston Field Office. In this role, you will analyze large and complex datasets to aid in cybercrime investigations, develop ETL processes, and collaborate closely with cybercrime investigators and forensic analysts to enhance investigative outcomes. Role - Analyze large and complex datasets to identify patterns, anomalies, and trends that can aid in cybercrime investigations. - Utilize advanced statistical methods and algorithms to extract actionable insights from data. - Develop and implement ETL (Extract, Transform, Load) processes to ensure data is efficiently processed and integrated. - Design and optimize data indexing and search processes to facilitate efficient data retrieval and discovery. - Work closely with cybercrime investigators and forensic analysts to provide data-driven insights that enhance investigative outcomes. - Participate in cross-functional teams to integrate data engineering methodologies into ongoing investigations. - Create data visualizations and dashboards to present findings in an easily interpretable manner for both technical and non-technical stakeholders. - Prepare detailed reports and presentations for internal and external audiences. - Contribute to the development and refinement of internal analytics tools and platforms, enhancing the overall effectiveness of data-driven investigations. - Develop prototypes and algorithms to support specific investigative needs. - Understand and apply Large Language Models (LLMs) to traditional Natural Language Processing (NLP) problems. - Utilize LLMs to triage unstructured text and extract relevant information for investigations. - Bachelor's degree in data science, Statistics, Computer Science, or a related field. - Minimum of 5+ years in data analytics or data engineering, preferably with a focus on cybercrime or financial investigations. - Proficiency in programming languages such as Python, R, or similar. - Proficiency with ETL processes and data integration. - Strong knowledge of data indexing, search, and discovery techniques. - Proficiency in database systems and SQL. - Strong analytical and problem-solving skills. - Familiarity with data visualization tools (e.g., Tableau, Power BI). - Excellent communication skills, with the ability to explain complex technical concepts to non-technical audiences. - Ability to work collaboratively in a team environment. - Experience in developing and implementing algorithms and prototypes. - Understanding of Large Language Models (LLMs) and their application to NLP problems. - Experience with traditional NLP techniques and tools. - Experience in cybercrime investigations or a related area. Salary/Rate: You know the salary range you are looking for, so let's talk after you fill out the application. Note: No 3rd party vendors or candidates US Citizenship Required Active DHS Suitability nice to have

Job Title: Data Scientist The Chord Energy Data Scientist role is a technical individual contributor role, focused on supporting business opportunities through the use of exploratory data analytics, machine learning models and generative AI opportunities. This position is located in Downtown Houston, TX. Hybrid work schedule is an option for remote work on Mondays and Fridays. Level and salary commensurate with experience. Essential Job Functions The primary responsibility involves leading and participating in multi-disciplinary projects aimed at providing business solutions to a diverse set of problems ranging from, but not limited to, production automation/optimization, drilling and completion process optimization, back-office process improvement and automation, dashboard generation and deployment, and computer vision aided operations. Additionally, the Data Scientist will contribute to the adoption of new technologies and best practices for analytical workflows. The ability to work well in a team and in support of core business functions will be critical to the success of this role. This job description is not intended to be an all-inclusive list of duties and responsibilities of the position. Incumbents will be required to follow any other job-related instructions and duties outside of their normal responsibilities as assigned by their supervisor. Minimum Qualifications Master's or Bachelor's degree in Data Science, Computer Science, or related field 5+ years in data science/ML (including time-series, geospatial, and predictive modeling) Proven experience and/or education in data analytics and management of large datasets Proficiency in Python (pandas, scikit-learn) and SQL; experience with Azure ML/MLflow and deploying models to production. Domain familiarity with upstream oil & gas workflows (subsurface and operations) and the ability to translate expert knowledge into features and experiments. Strong interpersonal and collaborative skills Demonstrated ability to work in a team-oriented environment Excellent presentation skills Ability to work in a fast-paced and fluid environment; flexible with the demands of a growing company Strong coaching, prioritization, and stakeholder-management skills; able to convert business problems into robust, scalable model solutions and communicate outcomes clearly. Ability to meet deadlines Physical Requirements and Working Conditions: Must possess mobility to work in a standard office setting and to use standard office equipment, including a computer, stamina to maintain attention to detail despite interruptions, strength to lift and carry files weighing up to 10 pounds; vision to read printed materials and a computer screen, and hearing and speech to communicate in person and over the telephone The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Preferred Qualifications Master's degree or PHD or certification in Data Science or Data Analytics Familiarity with additional programming languages (SQL, R, C++, etc.) Previous Oil and Gas operator experience Exposure to Petroleum Engineering and Geoscience workflows Exposure to the energy sector, particularly unconventional exploitation programs This role presents an exciting opportunity for a data scientist to contribute to the advancement of Chord's data science transformation, leveraging expertise in data analytics to drive innovation and optimize operational outcomes. EEO Statement: Chord Energy does not discriminate in employment on the basis of race, color, religion, sex (including pregnancy and gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factor.

We are looking for a Lead AI/Data Scientist for our top Energy Trading client. We need someone who is a do-er with proven execution experience. This is a full-time position without sponsorship. is onsite 5 days a week in Houston.

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

Description - HP is the world's leading personal systems and printing company, dedicated to creating technology that enriches lives everywhere. Our innovation thrives on the passion, talent, and curiosity of our people-each bringing unique perspectives, expertise, and ideas to shape the future of how the world works and lives. Join HP's Strategic Planning and Modeling (SPaM) Data Science Team - Where Vision Meets Impact Are you a visionary thinker with a passion for learning and innovation? Join our Strategic Planning and Modeling (SPaM) Data Science team, where we tackle complex supply chain challenges and drive strategic decision-making through advanced analytics. As a member of SPaM, you will: ✅ Evaluate supply chain investment and improvement opportunities. ✅ Develop cutting-edge predictive, prescriptive, and generative AI models to optimize business outcomes. ✅ Deliver strategic recommendations that shape HP's global supply chain. ✅ Collaborate with senior executives to set direction and drive innovation. ✅ Lead with technical and analytical expertise to translate theory into impactful business solutions through strong execution and cross-functional orchestration. At SPaM, we bring over 35 years of supply chain innovation. We value flexibility, invest in your growth through formal training and mentorship, and foster a culture where creativity and data-driven insights power the future. If pioneering data-based innovations to transform HP's supply chain excites you, we want to hear from you! Responsibilities Collaborate & Strategize: Work closely with SPaM team members and cross-functional partners to define business challenges, develop analytical frameworks, gather key data, evaluate solutions, and deliver well-supported recommendations to leadership. Drive Supply Chain Innovation: Develop and implement cutting-edge solutions in inventory management, working capital optimization, network design, forecasting, complexity reduction, product planning, manufacturing, and distribution to enhance efficiency and decision-making. Transform Data into Impact: Leverage data visualization techniques to craft compelling narratives that communicate insights, drive action, and demonstrate business value. Build & Scale Advanced Analytics Solutions: Design, deploy, and support predictive, prescriptive, and generative analytics models that drive measurable impact at scale. Enable Change & Adoption: Apply proven change management strategies to facilitate smooth adoption of new analytics-driven solutions across the organization. Stay Ahead of the Curve: Continuously enhance expertise in data science and supply chain management by staying informed on the latest advancements and industry trends. Education and Experience Required MS/PhD in a business analytics field (i.e. Industrial Engineering, Management Science, Operations Research, Statistics, Data Science) or MBA with Supply Chain or Operations concentration Operational experience in one of the following: inventory optimization, demand forecasting, network design, planning, forecasting, procurement, logistics, warranty, product quality, product variety management, or similar supply chain domain area 10+ years of experience Knowledge and Skills Expertise with inventory optimization math and deployment of the mathematical formulas into a business process Applied experience with machine learning and optimization on large datasets Proficient with Python, SQL, GitHub Co-Pilot, PowerBI, Excel Experience with GenAI Passion for data science & delivering data-driven outcomes Demonstrated innovation across the supply chain domains (Plan, Source, Make, Deliver, Return) Demonstrated practical experience in an operational environment Experience implementing and handing off operational analytical solutions to business users Demonstrated ability to deal well with ambiguity and work collaboratively in a fast-paced environment Demonstrated ability to communicate concisely with diplomacy, credibility, and confidence Experience with data visualization and data presentation in a clear and effective manner Experience leading, collaborating with, and delivering results in cross-functional teams Familiarity with statistics, forecasting, simulation, and spreadsheet modelling A desire to be a part of the HP team with a commitment to build upon our brand that is synonymous with innovation, trust, reliability, and sustainability The base pay range for this role is $147,050 to $232,850 annually with additional opportunities for pay in the form of bonus and/or equity (applies to US candidates only). Pay varies by work location, job-related knowledge, skills, and experience. Benefits HP offers a comprehensive benefits package for this position, including: Health insurance Dental insurance Vision insurance Long term/short term disability insurance Employee assistance program Flexible spending account Life insurance Generous time off policies, including: 4-12 weeks fully paid parental leave based on tenure 11 paid holidays Additional flexible paid vacation and sick leave (US benefits overview) The compensation and benefits information are accurate as of the date of this posting. The Company reserves the right to modify this information at any time, with or without notice, subject to applicable law. #LI-POST Job - Data & Information Technology Schedule - Full time Shift - No shift premium (United States of America) Travel - 25% Relocation - Not Specified Equal Opportunity Employer (EEO) - HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s). Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence. For more information, review HP's EEO Policy or read about your rights as an applicant under the law here: “Know Your Rights: Workplace Discrimination is Illegal"

Career CategoryInformation SystemsJob DescriptionJoin Amgen's Mission of Serving Patients At Amgen, if you feel like you're part of something bigger, it's because you are. Our shared mission-to serve patients living with serious illnesses-drives all that we do. Since 1980, we've helped pioneer the world of biotech in our fight against the world's toughest diseases. With our focus on four therapeutic areas -Oncology, Inflammation, General Medicine, and Rare Disease- we reach millions of patients each year. As a member of the Amgen team, you'll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives. Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you'll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career. Principal Data ScientistWhat you will do Let's do this. Let's change the world. In this vital role you will serve as a senior individual-contributor authority on semantic modeling, context engineering, and AI-first data science-enabling high-performing classical ML, reinforcement learning-informed approaches, and generative AI systems through well-architected context. This role functions as an “AI Context Architect” (titled as a Data Scientist): a semantic architect who can define domain entities (e.g., payer, provider, patient, product, site, indication) and the relationships between them, so that data + context reliably drive model reasoning, retrieval, and downstream decisions. You will design the semantic foundations that make AI systems accurate, explainable, governable, and performant-partnering with engineering, product, security/compliance, and domain teams across R&D, Manufacturing, and Commercial Roles & Responsibilities Semantic architecture & AI-first context modeling Define enterprise-grade semantic representations for healthcare/life-sciences concepts and specify how relationships and interactions are represented for AI consumption. Create and maintain semantic schemas / ontologies / knowledge-graph models that describe entities, attributes, constraints, and linkages-optimized for both analytics and AI reasoning. Establish context engineering standards: how data is shaped into prompts, tools, memory, retrieval indices, and structured outputs so models behave consistently across use cases. Feature engineering & model performance (core emphasis) Lead feature engineering strategy tied directly to model performance, including feature definition, transformations, leakage prevention, stability monitoring, and explainability. Perform exploratory data analysis on complex, high-dimensional datasets to identify predictive signals and context variables that improve model robustness and generalization. Context-aware ML, GenAI, and reinforcement learning-informed approaches Build and evaluate context-aware ML/GenAI solutions, integrating semantic layers with retrieval, tools, and structured outputs. Apply reinforcement learning concepts (reward modeling, policy optimization intuition, offline evaluation, exploration/exploitation framing) to improve decisioning, ranking, orchestration, and system behavior-without overfitting to short-term metrics. Prototype and benchmark algorithms and approaches (classical ML, deep learning, LLM-based reasoning) and advise on scalability and production readiness. Retrieval, knowledge, and governance foundations Architect and implement retrieval and memory patterns (RAG, vector stores, knowledge graphs, session memory). Define data quality and semantic quality gates (entity completeness, relationship validity, taxonomy drift, grounding coverage) that impact downstream model reliability. Cross-functional leadership Translate domain needs into semantic + AI roadmaps, aligning stakeholders on definitions, metrics, and tradeoffs. Act as a principal-level mentor and technical leader: establish standards, review semantic designs, and guide teams on best practices for context engineering and feature excellence. What we expect of you We are all different, yet we all use our unique contributions to serve patients. The professional we seek will have these qualifications. Basic Qualifications: Doctorate degree and 2 years of Data Science, Computer Science, Statistics, Applied Math, or related experience Or Master's degree and 4 years of Data Science, Computer Science, Statistics, Applied Math, or related experience Or Bachelor's degree and 6 years of Data Science, Computer Science, Statistics, Applied Math, or related experience Or Associate's degree and 10 years of Data Science, Computer Science, Statistics, Applied Math, or related experience Or High school diploma / GED and 12 years of Data Science, Computer Science, Statistics, Applied Math, or related experience Preferred Qualifications: 10-12+ years applying data science in enterprise environments with demonstrated principal-level influence (or equivalent depth of expertise). Deep expertise in semantic modeling: ontologies, taxonomies, entity resolution, knowledge graphs, metadata and data contracts-built for operational use. Strong understanding of machine learning fundamentals and performance drivers, especially feature engineering and evaluation rigor. Practical experience implementing RAG / retrieval / vector search / knowledge graph solutions with clear governance patterns. Working knowledge of reinforcement learning concepts and how they apply to ranking, orchestration, personalization, or decision systems (even if not “pure RL” production). Proficiency in Python (and strong comfort with modern data/ML stacks); ability to collaborate effectively with engineering teams on production concerns. Exceptional stakeholder management: can drive alignment on, relationships, and metrics, and communicate tradeoffs clearly. Good-to-Have Skills Experience in biotech/pharma and healthcare commercial concepts (payer/provider dynamics, formulary/coverage). Familiarity with agentic/tool-using LLM patterns, prompt management, and structured outputs. Experience with feature stores, ML observability, and robust evaluation tooling. Publications, conference talks, or thought leadership in semantic AI / knowledge systems / enterprise GenAI. Soft Skills: Excellent analytical and troubleshooting skills. Strong verbal and written communication skills Ability to work effectively with global, virtual teams High degree of initiative and self-motivation. Ability to manage multiple priorities successfully. Team-oriented, with a focus on achieving team goals. Ability to learn quickly, be organized and detail oriented. Strong presentation and public speaking skills. Certifications Cloud/AI certifications (AWS/Azure/GCP) are a plus. What you can expect of us As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, we'll support your journey every step of the way. The expected annual salary range for this role in the U.S. (excluding Puerto Rico) is posted. Actual salary will vary based on several factors including but not limited to, relevant skills, experience, and qualifications. In addition to the base salary, Amgen offers a Total Rewards Plan, based on eligibility, comprising of health and welfare plans for staff and eligible dependents, financial plans with opportunities to save towards retirement or other goals, work/life balance, and career development opportunities that may include: A comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions, group medical, dental and vision coverage, life and disability insurance, and flexible spending accounts A discretionary annual bonus program, or for field sales representatives, a sales-based incentive plan Stock-based long-term incentives Award-winning time-off plans Flexible work models where possible. Refer to the Work Location Type in the job posting to see if this applies. Apply now and make a lasting impact with the Amgen team.careers.amgen.com In any materials you submit, you may redact or remove age-identifying information such as age, date of birth, or dates of school attendance or graduation. You will not be penalized for redacting or removing this information. Application deadline Amgen does not have an application deadline for this position; we will continue accepting applications until we receive a sufficient number or select a candidate for the position. Sponsorship Sponsorship for this role is not guaranteed. As an organization dedicated to improving the quality of life for people around the world, Amgen fosters an inclusive environment of diverse, ethical, committed and highly accomplished people who respect each other and live the Amgen values to continue advancing science to serve patients. Together, we compete in the fight against serious disease. Amgen is an Equal Opportunity employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other basis protected by applicable law. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation. . Salary Range 163,136.00 USD - 214,390.00 USD

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.

Mindlance Inc. is a national recruiting company which partners with many of the leading employers across the country. Feel free to check us out at ************************* Job Description Role: Data Scientist Location: Houston, Texas 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 ************