Quantitative Researcher (Education & Employment) (Remote Eligible)

Mathematica Policy Research

7d•$100,000 - $135,000•Remote

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. Learn more about our benefits here: https://www.mathematica.org/career-opportunities/benefits-at-a-glance. We are looking for a quantitative researcher to join our division to support rigorous, data-driven, evidence-building activities. Our researchers support ongoing project teams in the planning and execution of projects for clients such as: The U.S. Departments of Education and Labor, Social Security Administration, the Bill and Melinda Gates Foundation, the Robert Wood Johnson Foundation, and numerous state and local agencies. Mathematica is seeking a researcher with specific expertise in quantitative research methods, causal inference, and social policy research, who will conduct studies and support program improvement and evaluation in the areas of employment, education, and disability. The following projects illustrate the type of work we currently have under way. Designing a quasi-experimental analysis to estimate the returns to postsecondary credentials relative to a high school diploma and examine variation across institution type and programs. Applying rigorous analytic methods to assess the effectiveness of linked, employment-focused reentry services delivered to individuals pre- and post-release from the criminal justice system Implementing randomized controlled trials to identify the impacts of return-to-work services for people with injuries and illnesses, and examining the factors that contribute to program effectiveness Conducting a descriptive study of a student loan program to understand how borrowing and repayment distress have responded to policy changes over time, and designing and assessing the feasibility of potential impact studies Examining participation and outcomes in a scholarship program for apprentices with financial need in eligible construction and industrial programs in Wisconsin. Helping states and school districts build capacity to use data and strengthen support for educators and students Conducting systematic reviews and meta-analyses to determine the effectiveness of interventions, programs, policies, and practices across a range of populations and policy areas

Requirements

Ph.D. in economics, public policy, sociology, education, statistics, data science/data analytics, or a related field. 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, including training in causal inference methodologies
Experience working with programming languages such as R, Python, or STATA
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

Nice To Haves

experience working at a human services program or agency, school district, state or federal government, or foundations
flexibility for a start date in early 2026.

Responsibilities

Participating in evaluation activities such as developing rigorous study designs, analyzing quantitative data from surveys and administrative sources, reviewing and synthesizing existing evidence, applying innovative methods such as machine-learning techniques, contributing to briefs and reports, and developing data visualizations to enhance the accessibility of findings.
Helping program administrators and policymakers make decisions by cleaning, organizing, analyzing, and presenting large amounts of data
Assessing the strength of study designs and summarizing large and diverse sets of existing research through systematic reviews and meta-analyses
Guiding program staff and policymakers in the use of evidence to make decisions about program selection and adaptation
Collaborating with state and local organizations through conducting evaluations or refining their programs
Presenting findings and disseminating information to policy, practitioner, and researcher audiences.