Quantitative Researcher - Public Health, Healthcare Evaluation, & Disability

Mathematica Inc•Ann Arbor, MI

3d•$100,000 - $140,000

About The Position

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 using data science and analytics. 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. Read more about our benefits here: https://www.mathematica.org/career-opportunities/benefits-at-a-glance.

Requirements

Ph.D. or equivalent in economics, public health, epidemiology, biostatistics, data science/data analytics, health services research, or other relevant discipline. In lieu of a PhD, a Masters’ degree with coursework in causal inference and demonstrated experience applying it to research will be considered equivalent.
Strong quantitative analytical skills.
Broad understanding of health policy issues in the United States
Experience working with programming languages, such as R, Python, or STATA, and with AI platforms, such as ChatGPT or Microsoft Copilot
Excellent written and oral communication skills, including an ability to translate complex research methods and findings for a practitioner and policy audience.
Ability to work well in teams.
Strong organizational skills and high level of attention to detail; flexibility to lead and manage multiple priorities, sometimes simultaneously, under deadlines.

Nice To Haves

Training in causal inference methodologies is strongly preferred.
Experience using health care and public health data sources (e.g., health care claims, electronic health records, national surveys) is strongly preferred.

Responsibilities

Collaborate with senior staff in a multidisciplinary environment to apply rigorous quantitative research methods, including study design, causal inference, data management, and statistical and econometric analysis for describing or evaluating programs and policies
Draft reports, present findings to policy and professional audiences, and publish in professional journals
Help develop proposals for new research projects
Contribute to the growth, expertise, and institutional knowledge of other research staff