Data Scientist (Remote Eligible)

Mathematica applies expertise at the intersection of data, methods,policy, and practice to improve well-being around the world. We collaborateclosely with public- and private-sector partners to translate big questionsinto deep insights that improve programs, refine strategies, and enhanceunderstanding. Our work yields actionable information to guide decisions inwide-ranging policy areas, from health, education, early childhood, and familysupport to nutrition, employment, disability, and international development. Mathematicaoffers our employees competitive salaries, and a comprehensive benefitspackage, as well as the advantages of being 100 percent employee owned. As anemployee stock owner, you will experience financial benefits of ESOP holdingsthat have increased in tandem with the company's growth and financial strength.You will also be part of an independent, employee-owned firm that is able todefine and further our mission, enhance our quality and accountability, andsteadily grow our financial strength. Learn more about our benefits here.

AtMathematica, we take pride in our commitment to diversity. Building aninclusive culture that draws on the individual strengths of employees fromdifferent ethnic backgrounds, cultures, lifestyles, abilities, and experienceis key to our success.

We arelooking for a Data Scientist who will derive meaning from data throughthe creation and deployment of data-driven approaches to solve problems andanswer important policy questions for clients. A Data Scientist owns dataprocessing and analysis tasks and supports more senior level data science staffin implementing statistical, machine learning, generative AI, and other datascience methods for use in research reports, internal systems, or clientsystems. Data Scientists will work on all aspects of the data science project lifecycle, including understanding client needs, building data pipelines,monitoring data quality, developing documentation, creating visualizations,brainstorming modeling approaches, and implementing those models. Our datascientists underpin our company's core offerings in program improvement, policyassessment, and data science, which yield crucial evidence and information forpolicy and decision makers. Thisposition will work remotely or flexibly in one of our office locations.

Exampleprojects include:

• Build and evaluate generative AI tools to extract clinically important information from unstructured doctors' notes, then use that information to construct predictive models and descriptive statistics to improve doctor decision-making and predictive accuracy.
• Evaluate and monitor the impacts of an alternative payment model for primary care in terms of care quality, cost, and health outcomes for diverse beneficiaries, using claims from thousands of primary care practices across the country. Use the same data to predict future hospital costs and behavior.
• Analyze nationwide geographic access to food retailers by integrating geospatial data on retailer locations, neighborhood demographics, demand, and social vulnerability. Apply network-based accessibility analyses to compare convenient access within and across states overall and by urbanicity and retailer type and develop interactive dashboards that help policymakers identify disparities and improve access to nutrition assistance.
• Use national survey data and grocery store purchase data to simulate realistic American diets and analyze their nutritional value. Analyze how that nutritional value compares to guidelines and what it suggests are practical, culturally aware food baskets consumers might purchase to meet the guidelines.
• Build knowledge synthesis solutions for government and foundation clients leveraging NLP and GenAI methods (knowledge graphs, Model Context Protocol, retrieval-augmented generation) to extract quantitative information (e.g., summary statistics, regression results) and contextual details (e.g., implementation specifics, focus group discussion themes) to distill large literatures into digestible datasets that support evidence-informed policymaking.
• Develop and evaluate a reproducible benchmarking pipeline to compare state healthcare spending against peer markets nationwide, harmonizing multi-source claims and Census data, applying statistical matching to select comparable regions, and normalizing spending through risk-adjusted regression models to support state rate-setting decisions.
• Build and evaluate interpretable machine learning models to predict clinical care tiers from health assessment data, supporting state healthcare program's transition to a new assessment tool.
• Partner with subject-matter experts to engineer clinically meaningful features from raw assessment items, and apply stratified sampling and diagnostics to deliver transparent models suited to high-stakes eligibility and reimbursement decisions.

Specifically,this Data Scientist contributes to team-based projects by:

• Conducting causal, predictive, and descriptive analyses
• Writing and maintaining programming systems in languages such as Python and R to build and evaluate models
• Developing reliable data pipelines to obtain, combine, and transform datasets on cloud, internal, and client servers
• Communicating technical results to diverse stakeholders including clients and cross-functional teams
• Developing and maintaining technical and methodological documentation
• Co-developing analysis plans with a senior data scientist or researcher
• Leading and managing small teams and tasks with oversight from a more senior staff member