Research Associate, Data Scientist, Research Analyst

The Social Science Research Council (SSRC) is an independent, international, nonprofit organization that works to mobilize social science knowledge for the public good. It advances interdisciplinary research in the social sciences and related disciplines through a wide variety of research programs, publications, workshops and conferences, fellowships and grants, and scholarly exchanges.

Measure of America (MOA) is an initiative of the SSRC dedicated to stimulating fact‑based public debate about issues of well‑being and access to opportunity in the United States. Through reports, interactive online tools, and evidence‑based research, Measure of America breathes life into numbers, using data to identify areas of need, pinpoint levers for change, and track progress over time. We measure what matters for human well‑being and develop tools for understanding opportunity and inequality in America.

Our work informs decisions made across the United States, has guided the allocation of hundreds of millions of dollars in public and private funding, is used as the foundation for community policy discussion and action, and shapes public debate in the highest‑profile media outlets in the nation. More information about the program is available sureofamerica.org.

Measure of America is seeking a Research Associate with strong quantitative social science skills and experience to join our high‑impact team. The Research Associate designs and independently executes quantitative research that undergirds our reports and interactive tools; contributes qualitative research and project management; and upholds high standards of accuracy and detail.

This role is ideal for a quantitative researcher who wants to own end‑to‑end work that directly shapes public‑facing research products. You’ll help build indicators and analyses that appear in MOA reports and interactive tools used by a broad audience of nonprofit leaders, municipalities, journalists, and policymakers—and you’ll work closely with a small, collaborative team where your work has clear visibility and impact.

• Lead quantitative research on well‑being, human flourishing, and access to opportunity (and related equity/public health/social and economic research topics)
• Own end‑to‑end analytic work streams for high‑visibility projects—from research design and data acquisition through cleaning, analysis, QA/reproducibility, and integration into reports and interactive tools
• Develop and communicate quantitative insights through clear data visualizations, written summaries, presentations, and web‑based outputs (e.g., mapping tools/pages), in collaboration with a small research team and external technical and design contractor
• Acquire, compile, and clean datasets from diverse public and private sources (especially U.S. Census/ACS and public health authorities)
• Apply appropriate statistical methods to large datasets (e.g., descriptive analysis and hypothesis testing) and document methodological choices and tradeoffs
• Build and maintain indicators/indices along with documentation, data‑quality validation to ensure transparent, replicable outputs
• Strengthen team‑wide research quality and speed by developing shared infrastructure (templates/codebase/pipelines/standards), serving as a cross‑project data and methods resource, and leading replication/QA reviews prior to publication
• Represent MOA externally through presentations to stakeholders at meetings and conferences
• Additional duties as assigned

• Required education and experience:
  • A master’s degree in a quantitative social science or related field (e.g., public health, sociology, economics, statistics, data science, or an interdisciplinary or related field with a strong quantitative component) AND
  • At least three years of full‑time quantitative social science or public health work experience
• Demonstrated experience compiling and analyzing quantitative data, including analyzing large public datasets
• Demonstrated project management skills, including coordinating timelines and stakeholders
• Natural attention to detail and drive for order that yields accuracy and reliability in the data and analysis…