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Researcher (Quantitative) **Job ID** 2318

Position Description:

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

Depending on projects and interests, duties might include:

+ 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.

Position 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

Of interest: 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.

This position offers an anticipated annual base salary range of $100,000 - $135,000. This position is eligible for an annual bonus opportunity based on individual and company performance.

Application Instructions:

+ Please submit a cover letter, resume, and a relevant work or writing sample. Letters of recommendation will be requested only for candidates who advance to the final stage of interviews. We will consider applications on a rolling basis and encourage you to apply early.

+ **If you are a current Mathematica employee** , please use the internal “job openings” portal, be sure to apply with your Mathematica email address, and contact your HR Business Partner after you have submitted your application.

+ **If you are a former Mathematica employee** , please select “employee referral” when prompted to identify how you heard about this opening. In the free-form field, please state that you are a former Mathematica employee.

We encourage applications from candidates who are interested in working in the below locations, but this position is also available to candidates who wish to work remotely from a different location.

Available Locations: Washington, DC; Princeton, NJ; Chicago, IL; Cambridge, MA; Ann Arbor, MI; Remote

We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state or local protected class.

At Mathematica, we understand the importance of building relationships with colleagues. If you’re not located near one of our offices but would like opportunities to meet up with co-workers, we offer coworking spaces where available. Ask your Talent Acquisition partner for more information about this opportunity and whether it’s an option in your area.

Any offer of employment will be contingent upon passing a background check. Various federal agencies with whom we contract require that staff successfully undergo security clearance as a condition of working on the project. If you are assigned to such a project, you will be required to obtain the requisite security clearance. Additionally, if you participate in/complete the application process and are denied, Mathematica may choose to terminate your employment.

Although Mathematica does not require vaccination from COVID-19 as a condition of employment, various projects or agencies may require documentation of vaccination (or an approved exception/accommodation).

We take pride in our employees and in their commitment to excellence. We encourage staff to collaborate in developing creative solutions to difficult problems and to share the responsibility and enjoyment of carrying out complex projects. This collegial spirit has helped us earn our reputation for innovative and high quality work.