Quantitative Researcher, Education & Employment (Remote Eligible)

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, National Science Foundation, philanthropic organizations such as the Bill and Melinda Gates 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 and education.

The following projects illustrate the type of work we currently have under way.

• Designing a quasi-experimental analysis to estimate the returns to postsecondary education relative to a high school diploma and examine variation across institution type and programs
• Applying rigorous analytic methods to assess the implementation and impacts of federal grants for workforce-aligned credentials on labor market outcomes
• 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
• Designing and deploying approaches that use artificial intelligence tools for data collection (such as literature search or web scraping), processing (for example, cleaning and coding) and preliminary analysis (for example, thematic analysis in qualitative data).
• 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.