Jobs · Analyst · Michigan

Human Services Researcher

Mathematica · Ann Arbor, MI · 3 wk ago
Analyst$100k–$135k/yrFull-time

About the Company

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 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.

About the Role

We are looking for researchers to join our vibrant and growing Human Services department. This position supports project teams within the department and across the company in the planning and execution of 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 an evolving policy and technology landscape. The role includes providing technical assistance focused on evaluation and program improvement to organizations serving families, youth, and adults; designing and carrying out research and evaluation, advising on strategy and policy, and linking and using data to answer complex policy-relevant questions. This role is primarily focused on programs designed to improve child welfare-related outcomes for children and families.

We will consider candidates with substantive expertise in a range of human services programs and policies, including child welfare, TANF, employment, early childhood, family strengthening, economic mobility, and related topics.

Responsibilities

The type of work we do includes activities such as:

  • Providing evaluation technical assistance to help grantees maintain high-quality impact and descriptive study designs and develop clear and specific performance measures.
  • Improving child welfare outcomes for children and families, with an emphasis on 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.
  • Conducting systematic reviews to determine the effectiveness of interventions, programs, and policies and practices across a range of populations and policy areas.
  • Building evidence around effective strategies for helping individuals with low incomes find and sustain employment.
  • Evaluating and providing technical assistance to states implementing TANF Pilots.
  • Evaluating and supporting competency-based professional development approaches for the infant and toddler workforce.
  • Enhancing and supporting the data analytic capacity of state child welfare and Medicaid agencies to improve the delivery of services.
  • Designing and implementing a nationally representative study of supports for family stability in Head Start.
  • Advising workforce development programs and state TANF agencies on evidence-based ways to increase program engagement and learn, innovate, and improve.
  • Evaluating programs that provide coaching for populations with barriers to employment.

Duties may include:

  • Providing technical assistance to programs serving youth and families to build evaluation capacity, use data, support continuous quality improvement, or engage in rapid cycle evaluation.
  • 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.
  • Assessing the strength of study designs and summarizing large and diverse sets of existing research through systematic evidence reviews and meta-analyses.
  • Applying innovative research approaches and advanced statistical methods to answer policy-relevant questions.
  • Working with data scientists to link and analyze administrative data.
  • 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 dashboards and visualizations.

Requirements

  • Ph.D. or Masters with equivalent experience in public policy, social work, sociology, psychology, education, economics, statistics, data science/data analytics, demography, or a related field.
  • Candidates with evidence of strong quantitative research skills will be prioritized. This includes experience with research design and analysis of primary, secondary, administrative, or survey data; current certification with What Works Clearinghouse evidence standards and knowledge of Prevention Services Clearinghouse evidence standards; mixed-methods experience is also valued.
  • Excellent written and oral communication skills, including an ability to translate complex research methods and findings for a practitioner and policy audience.
  • Willingness to learn and apply new techniques or technology, including AI.
  • Demonstrated ability to work effectively in multidisciplinary teams and contribute flexibly.

Preferred Qualifications

  • Experience directly providing evaluation technical assistance to federal grant recipients.
  • Experience with, or knowledge of, large-scale federal and/or other administrative data sets.

Pay

This position offers an anticipated base salary of $100,000 - $135,000 annually.

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