Data Scientist (Remote Eligible)

Mathematica applies expertise at the intersection of data, methods, policy, and practice to improve well-being around the world. We collaborate closely with public- and private-sector partners to translate big questions into deep insights that improve programs, refine strategies, and enhance understanding. Our work yields actionable information to guide decisions in wide-ranging policy areas, from health, education, early childhood, and family support to nutrition, employment, disability, and international development. Mathematica offers our employees competitive salaries, and a comprehensive benefits package, as well as the advantages of being 100 percent employee owned. As an employee stock owner, you will experience financial benefits of ESOP holdings that 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 to define and further our mission, enhance our quality and accountability, and steadily grow our financial strength. Learn more about our benefits here.

At Mathematica, we take pride in our commitment to diversity. Building an inclusive culture that draws on the individual strengths of employees from different ethnic backgrounds, cultures, lifestyles, abilities, and experience is key to our success.

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

The ideal candidate for this open Data Science position has a strong interest in applying their skills to healthcare and a strong statistical background in causal inference and supporting methodologies such as imputation, matching, weighting, regression, quasi-experimental methods, and synthetic-comparison methods, among others. In addition to the required technical skills below, our healthcare-focused data scientists strongly benefit from additional knowledge of SQL or Scala, experience with big data analysis platforms such as Databricks or Snowflake, and familiarity with healthcare datasets such as Medicare or Medicaid claims and enrollment data and electronic medical records.

Example projects include:

• 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.
• 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