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Quantitative Researcher, Human Services (Remote Eligible)

Role overview

Summary

This role focuses on conducting quantitative research and program evaluation within Mathematica's Human Services department. You will support project teams in delivering data-driven insights for clients, addressing complex policy challenges across various topics such as employment and child welfare.

Qualifications

  • Expertise in quantitative research methods and causal inference.
  • Experience in policy research and program evaluation.
  • Proficiency in statistical and econometric analysis.
  • Preferred: Familiarity with data visualization platforms and emerging analytic approaches.
  • Preferred: Ability to work in a multidisciplinary environment.

Responsibilities

  • Collaborate with senior staff to apply quantitative research methods for program and policy evaluation.
  • Design and implement mixed-methods evaluations, including data collection.
  • Synthesize and present data in accessible formats for diverse audiences.
  • Guide program staff and policymakers in using evidence for decision-making.

Hard skills

Other skills

  • Collaboration
  • Communication
  • Adaptability
  • Problem Solving

About the company

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Mathematica

  • Research & Scientific Services
  • Large
  • 1,001–5,000
As a partner to organizations around the world committed to improving public well-being, Mathematica uses social science, data science, digital solutions, and technology to build knowledge, evidence, and action-ready insights. From climate change mitigation to pandemic response, from improving patient care to closing opportunity gaps, we’re proud to be partners in progress on environmentally conscious, socially responsible, and sustainable solutions to build a more equitable and just world.

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Job description

Mathematica is hiring researchers to join our vibrant and growing Human Services department. We are seeking candidates with expertise in quantitative research methods, causal inference, and policy research to conduct studies and support program evaluation across a range of topics, including TANF, employment, child welfare, early childhood, family strengthening, and economic mobility.  

This position supports project teams within the department and across the company in the planning and execution of rigorous, data-driven projects for clients such as, the U.S. Department of Health and Human Services, state and local agencies, and Foundations and nonprofits. Mathematica is seeking researchers who are excited to solve complex policy and programmatic challenges in ways that are evidence- and data-driven, and who can agilely adapt to and evolving policy and technology landscape.  

The type of work we do includes activities such as: 

  • Evaluating programs that focus on topics such as healthy marriage and relationship education and teen pregnancy prevention using randomized controlled trials
  • Designing and implementing a nationally representative study of supports for family stability in Head Start
  • Conducting systematic evidence reviews of studies that focus on home visiting, teen pregnancy prevention, and employment
  • Improving child welfare outcomes for children and families, with an emphasis on linking administrative data and strategies to increase permanency and enhance the safety of children who are at risk of out-of-home placements
  • Using predictive analytics to improve outcomes for children and families
  • Building evidence around effective strategies for helping individuals with low incomes find and sustain employment
  • Enhancing and supporting the data analytic capacity of state child welfare and Medicaid agencies to improve the delivery of services
  • Advising agencies on evidence-based ways to increase program engagement and learn, innovate, and improve

Responsibilities may include:  

  • 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
  • Learning and applying new methods, tools, and technologies, including AI-enabled tools, data visualization platforms, and emerging analytic approaches
  • Designing rigorous mixed-methods evaluations, including primary and secondary data collection 
  • Applying innovative research approaches and advanced statistical methods to answer policy-relevant questions
  • Working with data scientists to link and analyze administrative data
  • Helping to develop proposals for new research projects 
  • Guiding program staff and policymakers in the use of evidence to make decisions about program selection and adaptation 
  • Synthesizing and presenting data in accessible formats for a variety of audiences, including writing briefs, reports, blogs, and articles; and developing interactive data dashboard and visualizations

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