Data scientist jobs in Texas City, TX - 140 jobs

We are seeking a Data Science Intern to assist with data preparation, analysis, and modeling tasks that support our manufacturing operations. This is a hands-on role where you will work closely with a data scientist to complete specific projects and deliver actionable insights. What You Will Do Clean and organize raw data from various sources for analysis. Perform exploratory data analysis (EDA) to identify patterns and trends. Create visualizations and dashboards to communicate insights clearly. Assist in building and testing machine learning models for predictive analytics. Document workflows and maintain clear records of analysis steps. Support ad-hoc data tasks as needed. This position is on-site in Beaumont or Houston, with potential for hybrid flexibility after onboarding. Qualifications Currently enrolled in an accredited university (Junior level or higher) in Data Science, Computer Science, Statistics, or related field. Basic knowledge of Python for data analysis and visualization. Familiarity with pandas, matplotlib/seaborn, or similar libraries. Understanding of data cleaning and exploratory analysis concepts. Strong analytical thinking and attention to detail. Ability to work independently and follow guidance on project priorities. Excellent communication skills for documenting and presenting findings. Preferred Skills Exposure to machine learning libraries (scikit-learn, TensorFlow, etc.). Experience with SQL or database querying. Familiarity with data visualization tools (Power BI). Ready to apply your skills and make an impact? Email me your resume!

Job DescriptionBenefits: 401(k) Competitive salary Dental insurance Health insurance Paid time off A Lead Data Scientist is responsible for managing data science projects, leading a team, and utilizing advanced analytics to drive business decisions and product improvements. Key Responsibilities Team Management: Lead and mentor a team of data scientists, machine learning engineers, and big data specialists to foster professional growth and collaboration. Project Planning: Oversee the planning and execution of data science projects, ensuring alignment with organizational goals and objectives. Model Development: Build and optimize analytical models using machine learning, natural language processing, and statistical techniques to derive insights from large datasets. Data Analysis: Analyze various data sources, including procurement, supply chain, and healthcare data, to inform business strategies and product development. Problem Solving: Identify and address data development challenges, proposing innovative solutions to enhance data utilization across the organization. Methodology Development: Lead the development and maintenance of methodologies that support product offerings, including statistical modeling and time-series analysis. Stakeholder Collaboration: Work closely with business leaders and other departments to communicate analytical findings and drive data-driven decision-making. Required Skills and Qualifications Educational Background: Typically requires a Masters or Ph.D. in Statistics, Computer Science, Mathematics, or a related field. Technical Expertise: Proficiency in data manipulation, visualization, and machine learning techniques, with experience in programming languages such as Python, R, or SQL. Analytical Skills: Strong problem-solving abilities and a knack for statistical analysis to interpret complex data sets effectively. Leadership Skills: Experience in managing teams and projects, with the ability to mentor junior data scientists and foster a collaborative environment. Communication Skills: Excellent verbal and written communication skills to convey complex analytical concepts to non-technical stakeholders. Salary Expectations $125,000 - $140,000

The Associate Data Scientist's primary responsibility will be to assist in the computational analysis of spatial single-cell transcriptomic and proteomic data from patient tumors generated from platforms such as CosMx Spatial Molecular Imager. Analyses will involve identifying spatially localized cellular niches, characterizing immune and epithelial cell states, modeling cell-cell communication, and uncovering pathways through which host-microbe interactions influence tumor biology. *The ideal candidate will have experience in cancer biology omics. * *At MD Anderson, we offer careers built on care, growth, and balance. Our employees enjoy a benefits package designed to support every stage of life, starting on day one.* - Paid employee medical benefits (zero premium) starting on first day for employees who work 30 or more hours per week - Group Dental, Vision, Life, AD&D and Disability coverage - Paid time off (PTO) and Extended Illness Bank (EIB) paid leave accruals - Paid institutional holidays, wellness leave, childcare leave, and other paid leave programs - Tuition Assistance Program after six months of service - Teachers Retirement System defined-benefit pension plan and two voluntary retirement plans - Employer paid life, AD&D and an illness-related reduced salary pay program - Extensive wellness, recognition, fitness, employee health programs and employee resource groups *Key Functions * *1. Analyzation and Integration Single-Cell and Spatial Omics Data* Process and interpret single-cell RNA-seq and spatial proteomic and transcriptomic datasets to identify cellular states and tumor microenvironment features. Integrate multimodal data from platforms such as CosMx, MIBI, STOmics or GeoMx to uncover spatial niches and model cell-cell and host-microbe interactions. Apply analytical methods including clustering, differential expression, trajectory inference, and spatial proximity analyses. *2. Computational Pipelines for Biological Insight Development* Build, document, and maintain reproducible analysis pipelines in Python and R for high-dimensional omics datasets. Conduct pathway enrichment and network-based analyses to identify biologically relevant trends in cancer and immune responses. Generate publication-ready visualizations and figures that communicate key findings for manuscripts, grants, and presentations. *3. Collaborate, Communicate, and Document Research Outputs* Partner with interdisciplinary team members to interpret data, support experimental planning, and contribute to scientific publications. Present analytical results in lab meetings and project discussions to inform ongoing research directions. Maintain well-organized code, metadata, and supplementary materials to support reproducibility and data sharing. *Education* Required: Bachelor's degree in Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Statistics, Computer Science, Computational Biology, or related field. *Experience* Required: Two years experience in scientific software or industry development/analysis. Preferred: Knowledge of transcriptomics and proteomics is a plus The University of Texas MD Anderson Cancer Center offers excellent ******************************************************************************************************* tuition benefits, educational opportunities, and individual and team recognition. This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening. The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment. It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state, or local laws unless such distinction is required by law.************************************************************************************************ Additional Information * Requisition ID: 176433 * Employment Status: Full-Time * Employee Status: Regular * Work Week: Day/Evening, Days * Minimum Salary: US Dollar (USD) 88,000 * Midpoint Salary: US Dollar (USD) 110,000 * Maximum Salary : US Dollar (USD) 132,000 * FLSA: exempt and not eligible for overtime pay * Fund Type: Soft * Work Location: Hybrid Onsite/Remote * Pivotal Position: Yes * Referral Bonus Available?: Yes * Relocation Assistance Available?: Yes \#LI-Hybrid

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

About the Role As an Energy Data Scientist, you will play a key role in analyzing and optimizing energy systems, predicting demand, and supporting sustainability initiatives through advanced data analytics and machine learning. This position requires a combination of strong analytical skills, knowledge of energy systems, and expertise in machine learning to enhance energy efficiency and innovation. Responsibilities Collect, clean, and analyze large datasets from energy sources (e.g., grid data, renewable sources, smart meters). Develop predictive models for energy consumption, generation forecasting, and load balancing. Use machine learning and statistical models to optimize energy distribution and storage. Perform time-series analysis to predict demand fluctuations and prevent energy shortfalls or surpluses. Work closely with engineering teams to implement data-driven solutions across energy systems. Conduct exploratory data analysis (EDA) to uncover insights and recommend actionable strategies. Develop and maintain data pipelines, ensuring real-time access to data for model training and validation. Communicate findings and present data insights to stakeholders and decision-makers. Required Qualifications Education: Bachelors degree in Data Science, Computer Science, Engineering, Statistics, or a related field (Master's or Ph.D. preferred). Experience: 3+ years of experience in data science, with a focus on energy or utilities preferred. Technical Skills: Proficiency in Python, R, SQL, and data visualization tools (e.g., Tableau, Power BI). Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-Learn. Strong understanding of time-series analysis, statistical modeling, and predictive analytics. Familiarity with big data tools like Hadoop, Spark, or cloud-based solutions (e.g., AWS, Azure). Domain Knowledge: Understanding of energy systems, power grids, and renewable energy sources is a strong advantage. Preferred Skills Experience with optimization algorithms and real-time data processing. Familiarity with industrial IoT data and sensor technologies. Knowledge of carbon emissions tracking and sustainability metrics. Ability to communicate complex technical findings to non-technical stakeholders. Working Place: Houston, TX

Role: Data Scientist This resource will work specifically on anomaly detection within one of our plant operations projects. The purpose of this project is to scale anomaly detection models for the transformer fault POC and add new models relating to thermal data. Other projects as required to require skills in forecasting and linear regression. Essential Duties/Responsibilities: Understanding of machine learning and deep learning models to select and implement for prediction, classification, and clustering Understanding of the business context of projects and able to identify areas where models will be less predictive or have caveats to their predictive powers Ability to communicate and establish good relations with multi-disciplinary teams Expertise with neural networks, specifically RNNs within the Keras/TensorFlow framework. Proficiency with Python, including pandas, scikit-learn Experience in PySpark Minimum Requirements: Bachelors degree in a quantitative field, such as Statistics, Mathematics, Computer Science, Economics, Engineering, or Operations Research required. 3+ years of experience in statistical modeling and quantitative analysis in industry or full-time academic research Preferred Qualifications: Advanced Degree (MS or PhD) in Statistics, Mathematics or Quantitative Marketing with a focus on machine learning is strongly preferred. Additional Knowledge, Skills and Abilities: Knowledge of power transformers, experience with electrical engineering. Prior experience predictive maintenance in a power or manufacturing environment. Experience with Databricks, AWS SageMaker and/or Google Vertex AI Comfortable working in Linux Experience with Git Experience with Docker containers Good communication skills

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.

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

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

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

People are our passion and purpose. Come work where you are valued for who you are, not just for what you can do. Remote Core Solutions provides tailored outsourcing and recruiting solutions, connecting high-performing talent with companies across a wide range of industries from startups to large enterprises. We take pride in matching candidates with roles where they can grow, innovate, and make an impact. About Our Client: Our client is a nationally recognized healthcare system focused on innovation, technology, and data-driven decision-making. Their enterprise data and analytics team supports transformative work across patient care, operations, and strategic initiatives. As they continue to invest in AI and data science, were helping them hire a dynamic Lead Data Scientist to spearhead strategic analytics projects, machine learning models, and executive-level insights across the organization. This role will be in person, in Houston, TX. About the Role: The Lead Data Scientist will lead critical enterprise-wide data science initiatives, manage high priority projects, and provide mentorship to junior data scientists. The ideal candidate is a hands-on builder who thrives at the intersection of healthcare, machine learning, and executive-level strategy. You'll be responsible for designing advanced models, leading stakeholder communication, and driving data science maturity across the organization. Responsibilities: Lead the design, development, and implementation of predictive and prescriptive data science models using healthcare and EHR datasets. Build, maintain, and validate machine learning algorithms for structured and unstructured data. Translate complex findings into actionable insights and present them to senior leadership and C-level executives. Develop custom data pipelines and oversee large-scale data set construction. Mentor junior data scientists and support ongoing training within the department. Serve as project lead on cross-functional initiatives involving clinical, finance, and operations data. Partner with key stakeholders to identify high-impact opportunities for analytics across departments. Maintain and optimize existing models, monitor model drift, and validate performance over time. Actively participate in vendor evaluations and provide recommendations for new tools and platforms. Ensure best practices in documentation, version control, and reproducibility across projects. Must-Haves: Bachelors Degree in a STEM related field (Science, Engineering, Mathematics, or Computer Science) Master's preferred. 7+ years of hands-on data science experience. Proven project leadership experience and ability to drive results independently. Strong communication skills with experience presenting to C-level stakeholders. Extensive experience building custom datasets and applying ML techniques (e.g., neural networks, regression models, clustering, forecasting). Cogito experience is required. AWS Certification is mandatory. Advanced experience with statistical programming (Python, R, or similar), SQL, and data visualization tools. Healthcare or hospital data environment experience preferred (e.g., EHR, revenue cycle, or clinical data). Interview Process: Recruiter Interview / Screening Hiring Manager Interview Final Panel Interview

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.

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

Description - This role is responsible for analyzing and interpreting complex data sets using statistical techniques to identify trends, patterns, and insights that can be used to form business decisions and improve organizational performance. The role brings cutting edge perspective on programming techniques for data exploration, mining, preparation, cleansing, manipulation, modeling and validation. The role explores potential opportunities for improving business outcomes with data analytics and improves productivity by recommending efficient, automated processes for large scale data analyses and model development. Responsibilities Leads data mining using modern tools and programming languages. Develops monitoring metrics to reflect real-world model performance and makes recommendations to shape the future direction of models and digital solutions. Delivers predictive and prescriptive models of high complexity to surface insights; drives action, defines success measures and tracks performance of models. Strategizes models to uncover patterns and predictions creating business value and innovation. Manages relationships with business partners to evaluate and foster data driven innovation, provides domain-specific expertise in cross-organization projects/initiatives. Ties insights into effective visualizations communicating business value and innovation potential. Works with development teams and business units to ensure models are scalable and can be implemented as part of the delivered solution. Leads project team(s) of data science professionals, assuring insights are communicated regularly and effectively, reviewing designs, models and data compliance. Represents the data science team for all phases of larger and more-complex development projects. Provides guidance, training and mentoring to less experienced staff members. Qualifications Passion for data science & delivering data driven outcomes. Expert knowledge of Python, SQL, and PySpark. Experience in one or more machine learning frameworks, such as Tensorflow/Keras, PyTorch, Spark MLlib, or Scikit-Learn. Ability to handle large amounts of structured and unstructured data and apply modern data transformation methodologies. Extensive experience using various machine learning algorithms (e.g., classification, regression, clustering) to develop and deploy predictive models Leads data science projects, assuring insights are communicated regularly and effectively, reviewing designs, models and data compliance. Delivers predictive and prescriptive models of high complexity to surface insights; drives action, defines success measures and tracks performance of models. Ability to uncover patterns and predictions from data to create business value and innovation. Strong analytical, problem-solving, and critical-thinking abilities. Ability to deal with ambiguity and work collaboratively in a high paced environment. Excellent interpersonal and project management skills; ability to work across in-person and virtual team environments. Experience visualizing data and conveying insights in a clear and effective manner What types of tools, software, hardware Programming Languages: Python, SQL Machine Learning Frameworks: Scikit-learn, Tensorflow, PyTorch, Pandas, Numpy Data Visualization: Power BI Preferred: Databricks, Microsoft Azure, Big Data, NLP Education, certifications, and areas of studies Four-year or Graduate Degree in Mathematics, Statistics, Computer Science, Data Science, or related field. Years of experience Typically has 7-10 years of work experience, preferably in data science, statistical modeling, machine learning, or a related field. Knowledge & Skills Data Science Machine Learning/AI Big Data Data Mining Deep Learning Data Visualization Programming Languages (Python, SQL) Statistics Predictive Modeling Time-Series Forecasting Cross-Org Skills • Effective Communication • Results Orientation • Learning Agility • Digital Fluency • Customer Centricity Impact & Scope • Impacts function and leads and/or provides expertise to functional project teams and may participate in cross-functional initiatives. Complexity • Works on complex problems where analysis of situations or data requires an in-depth evaluation of multiple factors. Disclaimer This job description describes the general nature and level of work performed in this role. It is not intended to be an exhaustive list of all duties, skills, responsibilities, knowledge, etc. These may be subject to change and additional functions may be assigned as needed by management. The pay range for this role is $130,700 to $205,200 USD annually with additional opportunities for pay in the form of bonus and/or equity (applies to United States of America 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 is 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. Job - Data & Information Technology Schedule - Full time Shift - No shift premium (United States of America) Travel - No Relocation - No 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"

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.

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

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.

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