"Health Economist, SCALE Lab"

Overview

The SCALE (State Collaborations to Advance Learning) initiative at Yale helps state-level social insurance programs-such as Medicaid and SNAP agencies-become more efficient and effective through data-driven, evidence-based insights.

Led by Yale Professors Chima Ndumele and Jacob Wallace, SCALE produces actionable research to support state decision-making, fosters partnerships between academics and policymakers, and delivers real-time support to states navigating the evolving challenges of Medicaid and other safety-net programs.

We are seeking a skilled economist to join the SCALE team and help advance its mission. Based at the Yale School of Public Health, the Health Economist will work closely with Professors Ndumele and Wallace, the Director of Research, and other SCALE team members on projects at the intersection of policy, research, and analytics. They will lead studies that apply advanced statistical, econometric, and machine learning methods to evaluate and improve Medicaid and other safety-net programs. The role includes close collaboration with Connecticut’s Department of Social Services (DSS), where SCALE analytics team members are also embedded. The Health Economist will collaborate with agency partners to link data systems, build infrastructure, and uncover new opportunities for policy evaluation. This position offers meaningful opportunities to contribute to peer-reviewed publications in top economics, clinical, and health policy journals, while supporting public programs in serving their communities more effectively.

This is an exciting opportunity for a mission-driven researcher with strong skills in causal inference and statistical programming (e.g., R or Python), who is eager to apply empirical methods to real-world policy challenges. The ideal candidate is fluent in working with large-scale health data, collaborates effectively with both technical and non-technical stakeholders, and is motivated to produce research which translates into real-world policy.

Required Skills and Abilities

1. Proven experience working with large, administrative (or transactional) data sets. Programming expertise in R, python, STATA or another statistical programming language.
2. Excellent communicator, with experience conveying complicated analyses to both technical and non-technical audiences.
3. Exceptional organization skills, and ability to prioritize and manage multiple projects simultaneously.
4. Excellent data literacy: able to triage data challenges appropriately to efficiently focus effort on the most promising research ideas.
5. Proven experience applying causal inference or econometric techniques (e.g., instrumental variables, difference-in-difference, regression discontinuity, randomized controlled designs) to evaluate the impacts of interventions.

Principal Responsibilities

1. Apply advanced econometric, statistical, and machine learning methods to descriptive, randomized, and quasi-experimental data settings.
2. Design analytic plans which connect data to economics research questions to evaluate policy impacts, distill learnings, and inform safety net program design.
3. Collaborate with state partners to build strong working relationships, surface and diagnose challenges, build infrastructure, and help translate analytic findings into actionable improvements in program design and delivery.
4. Customize the presentation of results, including data visualizations and written summaries, to meet the needs of technical and non-technical audiences.
5. Identify, build, and maintain data assets for research and policy analysis. Create expertise, documentation, standardized analyses, and best practices to improve the quality of research and ease at which new members can be onboarded to data systems.
6. Collaborate with and mentor junior team members (research fellows, pre-doctoral researchers, part-time students) to drive the research forward and foster a collaborative, high-performance culture.
7. Train and support analytic team members in programming and data management, supporting technical skills development, coding best practices, and workflows.
8. Contribute to or co-author published articles, policy briefs, presentations and grant proposals.
9. Identify areas of research that extend and enhance the SCALE research agenda.

Required Education and Experience

PhD in economics, statistics, mathematics, data science, health policy, or a related quantitative field. Experience working with large, administrative (or transactional) data sets. Experience applying causal inference or econometric techniques (e.g., instrumental variables, difference-in-difference, regression discontinuity, randomized controlled designs) to evaluate the impacts of interventions.

Preferred Education and Experience

1. At least 1 year of relevant experience.
2. Experience in health policy research, or work with state/federal policy partners.
3. Familiarity with administrative health care claims data, large-scale individual-level medical records, claims-based analyses, and data sets which contains 10 million+ observations.
4. Knowledge of the Medicaid program, social safety net, and healthcare landscape in the United States.
5. Experience working collaboratively, creating modular analytic tools and using git, to build reproducible and maintainable data science infrastructure.

Salary Range

$68,000.00 - $120,500.00

Location

60 College Street, New Haven, Connecticut

Work Model

Hybrid