Research Economist - Health Care Systems Research
Listed on 2026-01-25
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Research/Development
Data Scientist, Research Scientist, Public Health -
Healthcare
Data Scientist, Public Health
Overview
RTI International is an independent, scientific research institute dedicated to improving the human condition. Our vision is to address the world's most critical problems with technical and science-based solutions in pursuit of a better future. Clients rely on us to answer questions that demand an objective and multidisciplinary approach—one that integrates expertise across social, statistical, data, and laboratory sciences, engineering, and other technical disciplines to solve the world’s most challenging problems.
We believe in the promise of science and technical solutions, and we push ourselves every day to deliver on that promise for the good of people, communities, and businesses in the US and around the world. If you are looking for the opportunity to make a real difference, RTI is the place for you.
About the Hiring GroupRTI International’s Department of Health Care Systems Research has an opening for a Research Economist to serve as a task and project leader for evaluation, analysis, design, and implementation of innovative health care delivery policies, programs, and models.
As a Research Economist, you will provide cutting-edge analyses that will influence health care policy and health care system innovation, particularly within the Medicare and Medicaid programs. Using large health care datasets, you will design, evaluate, and support policies related to health care insurance, payment, and delivery models; managed care; health care financing, costs, utilization, and quality; health insurance coverage and access;
prescription drugs; and risk and case-mix adjustment through statistical analysis.
You will lead analytic projects as an integral part of a team, apply an in-depth understanding of critical health policy issues and methods, contribute to and lead proposals to funding entities, and publish and present on findings for scientific audiences.
This role is well-suited for economists and applied researchers with experience in academia, government, industry, or contract research who are interested in advancing evidence-based health policy.
Candidates may choose to work remotely within the United States or from RTI's headquarters in Research Triangle Park, NC.
What You'll Do- Lead and/or contribute to quantitative research and evaluation activities on a broad range of health policy and health services research topics.
- Design, specify and supervise descriptive and statistical analyses of large, complex datasets.
- Translate analytic findings into clear, actionable insights for technical, policy, and client audiences. Author technical reports, memoranda, articles, documentation, and regulations.
- Ensure high quality and accuracy of work products.
- Develop and manage project budgets, timelines, and plans to achieve goals within available resources.
- Supervise and manage research staff in completing project tasks.
- Communicate and negotiate work plans, timelines, budgets, and results with clients.
- Lead and/or contribute to technical proposals including methodological designs.
- Collaborate effectively within multidisciplinary teams of varying technical expertise.
- Maintain and deepen expertise in health care policy, research methods, and health care data sources.
Minimum Qualifications:
- PhD in economics, health policy, health services research, actuarial science, operations research, finance, or a related quantitative field with at least six years of relevant experience; or a Master’s degree in the same fields with at least 10 years of relevant experience; or a Bachelor’s degree in the same fields with at least 12 years of relevant experience.
- Demonstrated experience leading or substantially contributing to applied quantitative research and evaluation projects.
- Strong expertise in advanced micro-econometrics, simulation analysis, and program evaluation applied to real-world policy questions.
- Demonstrated experience applying causal and statistical inference methods to complex data.
- Ability to communicate (both written and verbal) complex technical concepts and information clearly and precisely to diverse audiences.
- Experience collaborating effectively within multidisciplinary teams.…
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