Data scientist jobs in League City, TX - 213 jobs

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

A large natural gas producer in Houston, which continues to build and expand its Commercial Trading/Origination teams for natural gas, LNG, and power, is seeking an experienced Data Scientist. The position is newly created for the Fundamental & Quantitative Analytics team; it will leverage energy data and advanced/novel modeling to drive insights that solve complex problems in underlying market fundamentals and drive growth in commercial operations revenue. Responsibilities include: Help to establish and architect an end-to-end advanced Data Science modeling function focused on data and models used for natural gas, LNG, and power trading and marketing/origination Working closely with the Data Engineer, develop and implement data acquisition strategies that incorporate vendor identification, web scraping, internal systems reviews, and unstructured data Lead model development using quantitative techniques, including machine learning, time series forecasting, optimization techniques, and statistical analysis Incorporate artificial intelligence and large language models Create robust processes and develop and deploy models into production with speed and accuracy Collaborate and coordinate with key stakeholders of Fundamental and Quantitative Analysis (Traders, Marketers/Originators, Commercial Analysts, IT, Data Engineers) to provide technical data solutions, including predictive models, risk assessment tools, optimization algorithms, and real-time monitoring systems Rapidly adapt models and insights to changing market conditions and emerging opportunities in natural gas, LNG, and power markets. Education and professional requirements include: Bachelor's degree in a quantitative field (Mathematics, Engineering, Statistics, Computer Science, etc.) ~2+ years of experience in a data science or quantitative role with exposure to energy commodities (natural gas, power markets, crude oil, LNG, NGL, or related markets) is required Experience with natural gas market fundamentals, including basis trading, pipeline systems, storage dynamics, and location-specific pricing data sets, is highly desired. Candidates from adjacent energy markets with strong technical skills will be considered. Demonstrated experience with advanced modeling techniques in machine learning, statistical modeling, optimization, and time series analysis Advanced technical skills, including Python/R, SQL, machine learning frameworks (scikit-learn, TensorFlow, PyTorch), and cloud computing platforms Experience with data acquisition methods, including APIs, web scraping, database management, schema development, and application of metadata layers Experience with both structured and unstructured data sources

# **Data Scientist \- Energy Trading** **Company:** Expand Energy Our core values - Stewardship, Character, Collaborate, Learn, Disrupt - are the lens through which we evaluate every business decision\. As a dynamic, growing company that offers extremely competitive compensation and benefits, our employees are our most valued assets and the foundation of Expands performance among our E&P competitors\. We seek applicants from all backgrounds to ensure we get the best, most creative talent on our team\. We realize that, historically, underrepresented groups feel the need to be 100% qualified in order to apply\. If you meet any combination of our requirements, we encourage you to apply\. We strive to hire people from a wide variety of backgrounds, not just because it's the right thing to do, but because it makes our company stronger\. ## **Job Summary** This isn't about maintaining existing systems \- you'll be architecting the analytical foundation that spots major market shifts or dislocations and drives real commercial value\. You'll lead the development of sophisticated models and analytical frameworks across natural gas, LNG, power, and related commodities while shaping the data strategy that supports critical trading decisions\. The role combines hands\-on advanced modeling with strategic thinking about data acquisition and architecture, with the autonomy to steer the ship and move quickly as both you and the business scale up\. Reporting structure within Fundamental & Quantitative Analytics team will be determined based on team composition and individual experience levels\. ## **Job Duties & Responsibilities** + Lead end\-to\-end advanced modeling initiatives from identifying data needs and acquisition strategies \(vendor sources, web scraping, internal systems, unstructured data\) through to deployment of production models + Develop and implement sophisticated analytical techniques including machine learning, time series forecasting, optimization models, and statistical analysis to address critical business themes with speed and accuracy + Serve as the technical visionary for applying novel analytical techniques and emerging technologies including machine learning, artificial intelligence, and large language models to energy commodity challenges + Collaborate closely with the Lead Data Engineer to develop integrated data strategy that supports both current analytical needs and cutting\-edge technological applications + Collaborate closely with data engineers and analysts to translate complex business requirements into technical data solutions, ensuring seamless integration from data acquisition to model deployment + Drive rapid response capabilities for market analysis, developing models and insights that can quickly adapt to changing market conditions and emerging opportunities + Build and maintain advanced analytical outputs including predictive models, risk assessment tools, optimization algorithms, and real\-time monitoring systems + Automate and streamline analytic processes and products + Establish best practices for modeling processes \(e\.g\. technical documentation, code review, version control, etc\.\) + Partner with the Director and analytics team members, traders, and commercial stakeholders to identify high\-impact analytical opportunities and translate findings into actionable business intelligence + Contribute to establishing best practices for model development, validation, and deployment while mentoring junior team members on advanced analytical techniques ## **Job Specific Skills** + Strong background in machine learning, statistical modeling, optimization, and time series analysis with proven ability to apply these techniques to real\-world business problems + Proficiency with advanced analytical tools including Python/R, SQL, machine learning frameworks \(scikit\-learn, TensorFlow, PyTorch\), and cloud computing platforms + Experience with diverse data acquisition and integration methods including APIs, web scraping; database management, schema development, and application of metadata layers; and working with both structured and unstructured data sources + Strong understanding of data architecture principles and ability to contribute to strategic decisions about data storage, processing, and modeling infrastructure, including cloud compute solutions \(Snowflake experience preferred but not required\) + Energy commodity market knowledge or demonstrated ability to quickly develop deep domain expertise in complex technical markets + Excellent communication skills with ability to translate complex analytical concepts into clear business insights for both technical and non\-technical stakeholders ## **Education** Minimum: High school diploma or GED Preferred: Bachelor's degree \- from accredited university \- Mathematics, Statistics, Analytics, Engineer, Computer Science, or related field Preferred: Master's degree \- from accredited university ## **Experience** Minimum: 2 \- 5 years related work experience Prior or current data science, quantitative analysis, or related technical roles with demonstrated expertise in advanced modeling techniques ## **Additional Qualifications** + Natural Gas Market Experience: Experience with natural gas market fundamentals including basis trading, pipeline systems, storage dynamics, and location\-specific pricing datasets\. Candidates from adjacent markets \(power, crude oil, financial commodities\) with strong analytical aptitude will be considered + Energy Trading Background: Experience at energy trading firms, commodity companies, or related commercial energy organizations with understanding of market dynamics and trading applications + Advanced Technical Skills: Experience with optimization software \(Gurobi, CPLEX\), advanced time series methods, or specialized domain modeling techniques + Data Strategy Experience: Track record of contributing to or leading data architecture decisions, platform selection, or analytical infrastructure development + Cross\-Functional Leadership: Experience working across technical and business teams to drive analytical initiatives from conception to implementation + Real\-Time Analytics: Experience developing models and systems that support time\-sensitive business decisions or trading applications + Emerging Technologies: Experience with or strong interest in applying novel technologies including large language models, advanced AI techniques, or cutting\-edge analytical methods to business applications Expand Energy takes necessary action to ensure that all applicants are treated without regard to their race, color, religion, sex, sexual orientation, age, gender identity, national origin, genetic information, disability, pregnancy, military or veteran status or any other protected characteristic as established by law\. Expand Energy Corporation's operations are focused on discovering and developing its large and geographically diverse resource base of unconventional oil and natural gas assets onshore in the United States\. **Nearest Major Market:** Houston **Job Segment:** Pipeline, Cloud, Quantitative Analyst, Statistics, Data Architect, Energy, Technology, Data

Our client is currently seeking a Data Scientist to join their team in Bangalore, India. The Data Scientist will be supporting automation projects utilizing large data sets to find opportunities for product and process optimization. They will work with stakeholders across the finance organization to identify opportunities to leverage company data to drive business solutions. Daily they will analyze data to create custom data models and algorithms to assess the effectiveness and accuracy of data sources and data gathering techniques. They will use predictive modeling to increase and optimize customer experience, revenue generation, ad targeting, and other business outcomes. They will be responsible for developing processes and tolls to monitor & analyze model performance and data accuracy. We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to ********************.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: **************************************************** Skills and Requirements 5+ years of experience as a Data Scientist Experience with Databricks, Python, and Power BI to manipulate data and draw insights from large data sets Understanding of the relationship between multiple data sets and how to build stories within Experience creating & using advanced machine learning algorithms & statistics (simulation, scenario analysis, modeling, etc.) Experience visualizing & presenting data for stakeholders using Power BI Experience with SQL and database management Bachelors degree Finance acumen/understanding of financial data

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

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

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 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,

Apply Description Job Title: DATA SCIENTIST Job Code: SES407 At Shell Energy Solutions, we believe there's a better way to power your business. Aligned with Shell's ambition to be a significant global power business and to become net zero by 2050, our cleaner, affordable, and simple solutions help companies manage their energy spend and plan their sustainability roadmap - a fresh approach for environmentally conscious businesses that are looking to boost their sustainability credentials. We also have set out to deliver the very best experience to our customers across all our channels. Shell Energy Solutions' mission is to deliver cleaner energy solutions for a brighter tomorrow by guiding customers toward a better energy future, enabling customer choice, and providing market-leading energy solutions. Going above and beyond for our customers is what we're all about and we have set out to deliver the very best experience to our customers across all our channels. But bigger challenges lie ahead, and we need to keep moving forward. Are you ready to help us get there? WHERE YOU FIT IN We are looking for a highly motivated individual with a genuine interest in energy, technology, and a passion to deliver products for a growing company. As the Data Scientist, you will own the end-to-end pipeline for load forecasting, encompassing development, deployment, and integration with downstream services. You will engage in cross-functional projects, collaborating within our team and various teams across the organization to ensure seamless integration and alignment with business objectives. Your work will directly impact the company's ability to make informed decisions, optimize operations, mitigate risks, and drive business growth. Reporting to the Senior Machine Learning Engineer, the role requires a self-motivated, dedicated, and responsible individual with the ability to perform well under pressure. JOB DUTIES & RESPONSIBILITIES (Main RESPONSIBILITIES and duties) Dig deep into available data to identify patterns, create datasets for predictive models, and improve the accuracy and precision of existing forecasting services Apply state-of-the-art machine learning and predictive modeling techniques to provide a deeper understanding of our customers and improve accuracy of our load forecasts Integrate the outcomes of load forecasting models into downstream services, such as gross profit reporting, to address key business needs Develop key metrics and visualizations to monitor and assess the performance of load forecasts, ensuring their accuracy and reliability Communicate modeling and engineering technical detail to stakeholders and partners to drive impact and facilitate decision making Other duties as assigned ESSENTIAL SKILLS AND EXPERIENCE (Skills Needed to be SUCCESSFUL) Successful job applicants will be able to perform these functions. Reasonable accommodations will be made to enable individuals with disabilities to perform the essential functions. 1-3 years of experience using SQL to query large datasets in cloud-based data warehouses and data lakes 1-3 years of experience with machine learning and statistical methods, bonus points if experience is in time-series forecasting 1-3 years of experience in machine learning development in Python Fluency with data visualization to communicate complex topics in approachable ways Strong background in mathematics and statistics Excellent communication skills, with the ability to deliver complicated findings and explain technical approaches to a variety of audiences Bonus if you have contextual work in the energy industry Bonus if you have experience with key data engineering frameworks: Apache Airflow, dbt, AWS services, Docker, Kubernetes Bonus if you have experience with software development lifecycle experience in GitHub (i.e. environment management, testing, deployment) Bonus if you have experience at a similar scale of data processing (Multi-TB/billion of rows) Bonus if you have experience with probabilistic modeling techniques such as Bayesian or conformal models Bonus if you have experience with machine learning frameworks: scikit-learn, Tensorflow/Keras, lifelines Bonus if you have experience with Hyper Parameter tuning frameworks such as Optuna Bonus if you have experience with cloud-based data intelligence platforms and ML tools such as Databricks, AWS Sagemaker, MLFlow Location and work SCHEDULE Required to be in-person in Houston, TX, through a hybrid workplace environment BENEFITS OF WORKING WITH Shell ENERGY Competitive Compensation Health Care - Medical/Dental/Vision/Prescription Drug Coverage 401(k) with Company Matching Contributions Flexible Spending Accounts (FSA) Health Savings Accounts (HSA) Disability Programs (STD & LTD) Employee Basic Term Life Insurance Generous Vacation & Company Holidays Flexible hybrid working schedule Training and coaching Tuition Reimbursement Paid Parental Leave And much more! SHELL ENERGY VALUES Shell Energy Solutions is a company with shared values. Honesty, integrity, and respect aren't simply a strapline; they are part of everything we do. What's more, Shell Energy Solutions is an equal opportunities company, and we place the highest possible value on the diversity of our people and our inclusive approach. Join us and you'll belong to a world where you are proud of your achievements and propel your career with global opportunities. We care deeply about fostering a truly diverse workplace. *Job descriptions are not intended as, nor should be construed to be, exhaustive lists of all responsibilities, skills, efforts, or working conditions associated with a job. They are intended to be accurate reflections of those principal job duties and responsibilities essential for making fair pay decisions about the job.

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.

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

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

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

Houston, TX (Onsite) | Contract | Mid-Senior Level | 1 Opening Pay Rate: $90/hour No Visa Sponsorship A leading organization in the energy sector is seeking an experienced Business Data Scientist III to support mission -critical commercial systems, analytics, and regulatory processes. This role is highly cross -functional, serving as the bridge between commercial teams, IT, regulatory stakeholders, and operations, with a strong focus on scheduling, contracting, analytics, and Electronic Bulletin Board (EBB) systems. This position is ideal for a seasoned professional with deep oil & gas industry experience, strong data analysis skills, and the ability to lead complex initiatives in a regulated, 24/7 operational environment. Position Overview The Business Data Scientist III provides advanced analytical, system, and process support for commercial and regulatory operations. The role includes ownership of data analysis, reporting, system enhancements, and continuous improvement initiatives, while also serving as a functional lead and subject matter expert for scheduling, contracting, and EBB -related systems. This role supports both internal and external customers and may involve 24/7 production support responsibilities for mission -critical systems. Key Responsibilities Provide 24/7 internal and external customer support for mission -critical commercial systems, serving as a liaison between business users and IT Act as a firewall between customers and IT by validating system issues, logging defects, coordinating testing, and ensuring compliant delivery Lead collaboration across commercial, IT, regulatory, and operations teams to design and implement business processes, workflows, and technology solutions Design and develop prototypes, proof of concepts, and analytical models for data mining and production use Develop, test, and implement analytical tools and dashboards to support commercial decision -making, customer insights, market trends, and process efficiencies Ensure Electronic Bulletin Board (EBB) systems operate in compliance with regulatory requirements, supporting enhancements tied to expansion and growth initiatives Serve as business lead for EBB, analytics, and data visualization enhancements, including requirements gathering, testing, deployment, and post -implementation support Act as a change agent by developing procedures, improving workflows, and identifying operational efficiencies Prepare and support revenue budgeting, forecasting, and monthly reporting for stakeholders Perform statistical analysis and leverage data to drive insights and predictive outcomes RequirementsRequired Qualifications Bachelor's degree in Accounting, Finance, Economics, Engineering, or a related field (Master's degree preferred) Minimum 6+ years of experience in the energy industry (oil & gas) Strong understanding of scheduling and contracting processes (pre -flow, flow, post -flow) Hands -on experience with Electronic Bulletin Board (EBB) systems Experience supporting 24/7 mission -critical systems Advanced proficiency in Microsoft Excel (pivot tables, macros, complex formulas) Strong experience with Power BI or equivalent business intelligence tools Ability to pull and analyze complex data from relational databases Proven ability to perform statistical analysis Experience leading or coordinating cross -functional teams with competing priorities Preferred Skills Knowledge of tariffs, rates, and regulatory compliance frameworks Familiarity with machine learning-based analytical tools Experience acting as a subject matter expert for commercial or operational systems

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"

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.

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

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

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