Data scientist jobs in Galveston, TX - 176 jobs

The Gynecologic Oncology and Reproductive Medicine department at MD Anderson's Cancer center is internationally renowned for research-driven patient care, specializing in the medical and surgical treatment of all types of gynecologic cancers including ovarian, vaginal, vulvar, endometrial and cervical cancers, as well as malignant ovarian germ-cell tumors, ovarian sex-cord stromal tumors, borderline tumors of the ovary, cervical intraepithelial neoplasia, human papillomavirus and gestational trophoblastic disease. The ideal candidate experience in analyzing spatial biology datasets (proteomics, metabolomic and transcriptomics). Salary range: Minimum $88,000.00 - Midpoint $110,000.00 - Maximum $132,000.00 *KEY RESPONSIBILITIES* *1. Computational Analysis & Pipeline Development* * Assist in the analysis, design and development of pipelines, algorithms and software for the analysis, exploration, and visualization of data generated using exome/whole genome sequencing, RNA-seq, ChIP-seq, ATAC-sequencing, chromatin conformation capture sequencing (e.g. Hi-C and similar methods) and spatial transcriptomics in a timely fashion. * Apply statistical and machine learning techniques to derive insights from complex, high-dimensional datasets, including in-house and public data (e.g., TCGA, CCLE, GTEx, GEO). * Run workflows for somatic mutation calling, copy number analysis, transcriptional profiling, clonality estimation, and mutational phylogeny inference on matched tumor/normal and longitudinal samples. * Run workflows for protein and metabolites analyses and integrate these datasets with abovementioned transcriptomics profiles. * Independently plan and adapt novel computational approaches to support evolving research needs and emerging experimental technologies in genomics, spatial, and single-cell omics. *2. Workflow Development, Data Management & Reproducibility* * With direction, develops and maintains bioinformatics tools and infrastructure using Python, R, Docker, Conda and other tools; create well-organized, reusable, and user-friendly workflows to support lab-wide analyses. * Generate custom visualizations and perform downstream analyses including gene expression profiling, mutation analysis, gene set enrichment, pathway analysis, protein and metabolomic analyses. * Ensure reproducibility and transparency by organizing data, documenting code, version-controlling pipelines, and maintaining clear scientific records in notebooks and shared repositories. * Contribute to the implementation of robust data stewardship practices and help maintain a scalable, collaborative analysis environment leveraging high-performance computing (HPC) systems. *3. Collaboration, Communication & Scientific Engagement* * Collaborate with experimental biologists, wet lab members, data scientists, and cross-functional institutional teams to integrate omics data with biological and clinical datasets and harmonize metadata across studies. * Assist with the preparation of manuscripts, figures, abstracts, grant proposals, and internal reports as well as for presentation at lab meetings, departmental reviews, and institutional events. * Communicate complex analytical findings effectively to both technical and non-technical audiences through presentations, visual summaries, and written reports. * Conduct literature reviews and stay current with emerging tools and trends in genomics, computational biology, and biomedical data science to inform pipeline development and project planning. * Support mentoring and onboarding of students, fellows, and research personnel by contributing to training in computational methods and analytical workflows. * Performs other duties as assigned. *EDUCATION* *Education Required: *Bachelor's degree in Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Statistics, Computer Science, Computational Biology, or related field. *EXPERIENCE* *Experience Required: *Two years experience in scientific software or industry development/analysis. *Experience Preferred: *Experience in analyzing spatial biology datasets (proteomics, metabolomic and transcriptomics). 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: 178221 * Employment Status: Full-Time * Employee Status: Regular * Work Week: 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

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.

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

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.

12-month contract 3x a week onsite Key Responsibilities: * Provides support to internal and external customers, working with IT to identify system-related issues and functions as a project lead to organize and develop project requirements, develop and complete testing plans, and follow-up on any fall-out after project implementation * Proper support should work as a firewall between the customers and IT to verify that issues are indeed system related. Identified defects should be logged, tracked, tested and delivered in accordance with its customer impact and compliance risk * Drives collaboration between all commercial areas, IT, and rates & regulatory, acting as a go-between to provide solutions for all groups that interact, directly or indirectly, with the system(s). * Provides support for the creation and implementation of business processes, workflow, technology solutions and technology frameworks * Design and develop prototypes and proof of concepts for modelling, data mining, and production purposes. * Support, design, develop, test and implement tools for Marketing Services Reps (G&P - Distribution, Commercial, and Commodity Ops) to analyze historical data for data inquiries, customer focus, market orientation, process and tariff (TGOM only) efficiencies and predict future behaviour of customers to drive commercial decisions. * Ensures the EBB (proprietary and public) operates in compliance with all regulations using standard methodologies with an eye toward continuous improvement. * Completes all EBB changes needed to ensure continued growth of company, including working closely with Business Development, Marketing Services, and Corporate Strategic Development to ensure that all expansion project requirements are detailed far in advance of the project's in-service date * Act as a change agent and assist in the development of processes and procedures to assist the team in finding efficiencies by learning to become a Subject Matter Expert (SME) for functional areas of the system * Act as the business lead for all EBB and data visualization and analytics modifications and enhancements. * Function as a team leader to organize/develop project requirements, provide quality construction guidelines, develop and execute testing plans, and follow-up on any fall-out after project implementation. * Prepares/supports revenue budget and forecasting; prepares and provides monthly reporting for stakeholders. * Drive collaboration between all commercial areas, IT, regulatory, and operations. * Acting as a go-between within company to provide solutions for all groups that interact, directly or indirectly, with the system(s). Required Qualifications: * Bachelor's degree in accounting, Finance, Economics or Engineering related field. Master's degree is preferred * Minimum 6 years' experience in energy industry (oil and gas) * Experience leading a diverse team, with management oversight, of employees with competing interests. Ability to pivot between topics quickly and identify the cost-effective most agreeable solution. * A thorough understanding of scheduling/contracting processes with an emphasis on one area (pre-flow/flow/post-flow). * Ability to pull complex database information and have a rudimentary understanding of relational databases. * Ability to perform statistical analysis * Advanced Excel pivot and/or Power BI skills * Knowledge of machine learning-based tools is a plus Apex Systems is a world-class IT services company that serves thousands of clients across the globe. When you join Apex, you become part of a team that values innovation, collaboration, and continuous learning. We offer quality career resources, training, certifications, development opportunities, and a comprehensive benefits package. Our commitment to excellence is reflected in many awards, including ClearlyRated's Best of Staffing in Talent Satisfaction in the United States and Great Place to Work in the United Kingdom and Mexico. Apex uses a virtual recruiter as part of the application process. Click here for more details. Apex Benefits Overview: Apex offers a range of supplemental benefits, including medical, dental, vision, life, disability, and other insurance plans that offer an optional layer of financial protection. We offer an ESPP (employee stock purchase program) and a 401K program which allows you to contribute typically within 30 days of starting, with a company match after 12 months of tenure. Apex also offers a HSA (Health Savings Account on the HDHP plan), a SupportLinc Employee Assistance Program (EAP) with up to 8 free counseling sessions, a corporate discount savings program and other discounts. In terms of professional development, Apex hosts an on-demand training program, provides access to certification prep and a library of technical and leadership courses/books/seminars once you have 6+ months of tenure, and certification discounts and other perks to associations that include CompTIA and IIBA. Apex has a dedicated customer service team for our Consultants that can address questions around benefits and other resources, as well as a certified Career Coach. You can access a full list of our benefits, programs, support teams and resources within our 'Welcome Packet' as well, which an Apex team member can provide. Employee Type: Contract Location: Houston, TX, US Job Type: Date Posted: January 7, 2026 Similar Jobs * Data Scientist * Data Scientist * IT Manager Data Scientist * Senior Data Scientist * Data Engineer III

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

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.

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

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

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,

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

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

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

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

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