Quantitative Researcher, Human Services (Remote Eligible)
About The Position
Mathematica is hiring researchers for its Human Services department to conduct quantitative research, causal inference, and policy research, and to support program evaluation across topics including TANF, employment, child welfare, early childhood, family strengthening, and economic mobility. The role supports multidisciplinary project teams across the company in planning and executing rigorous, data-driven projects for clients such as the U.S. Department of Health and Human Services, state and local agencies, foundations, and nonprofits. The work addresses complex policy and program challenges through evidence and data. Examples include evaluating programs with randomized controlled trials; designing nationally representative studies; conducting systematic evidence reviews; linking administrative data to improve child welfare outcomes; applying predictive analytics; building evidence on employment strategies; strengthening state agencies’ analytic capacity; and advising agencies on evidence-based program improvement. The researcher collaborates with senior staff, program staff, policymakers, data scientists, and clients. The position involves applying and learning research methods and technologies, designing mixed-methods evaluations, analyzing administrative data, contributing to proposals, and communicating findings in accessible formats. The position is remote eligible; Mathematica may offer coworking spaces where available. Employment offers are contingent on passing a background check, and some projects may require security clearance.
Requirements
- Ph.D. or equivalent in economics, psychology, sociology, statistics, data science/data analytics, demography, or a related field; a master's degree with coursework in causal inference and demonstrated experience applying it to research may be considered equivalent.
- Strong quantitative analytical skills.
- Experience working with programming languages such as R, Python, or STATA.
- Willingness to learn and apply new techniques or technology, including AI.
- Excellent written and oral communication skills, including the ability to translate complex research methods and findings for practitioner and policy audiences.
- Submit a cover letter, CV, and writing sample or job market paper with the application.
Nice To Haves
- Training in causal inference methodologies is strongly preferred.
- Understanding of federal human services policies and programs is strongly preferred.
- Experience with or knowledge of large-scale federal and/or other administrative datasets is desirable.
Responsibilities
- Collaborate with senior staff in a multidisciplinary environment to apply quantitative research methods, including study design, causal inference, data management, and statistical and econometric analysis.
- Learn and apply new methods, tools, and technologies, including AI-enabled tools, data visualization platforms, and emerging analytic approaches.
- Design rigorous mixed-methods evaluations, including primary and secondary data collection.
- Apply innovative research approaches and advanced statistical methods to answer policy-relevant questions.
- Work with data scientists to link and analyze administrative data.
- Help develop proposals for new research projects.
- Guide program staff and policymakers in using evidence to make decisions about program selection and adaptation.
- Synthesize and present data for varied audiences through briefs, reports, blogs, articles, interactive dashboards, and visualizations.
- Conduct and support research and evaluation across human services topics, including TANF, employment, child welfare, early childhood, family strengthening, and economic mobility.
Benefits
- Competitive salaries and a comprehensive benefits package.
- Employee ownership through ESOP holdings, with financial benefits tied to the company’s growth and financial strength.
- Coworking spaces where available for employees who are not located near an office.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
Ph.D. or professional degree
