Research Scientist

Education Analytics (EA) is a non-profit organization that uses rigorous data analysis to inform education research, management, and policy decisions. Our staff is a group of highly motivated, energetic, passionate researchers and analysts who work with school districts, states, and foundation partners across the U.S. to identify innovative ways to improve education systems

We are seeking an experienced researcher with either a Ph.D. in economics, or a Ph.D. in statistics or a related field, who specializes in econometrics, applied statistics, or related quantitative methods. The Research Scientist at EA collaborates with external project partners, other researchers, data strategists, analysts, and policymakers. The position will report to the Research Manager and Chief Research Officer and will play a substantial role in directing various programs of research.

This position would be expected to work at our physical location in Madison, Wisconsin.

Specific Research Scientist responsibilities include:

  • Developing statistical models for education policy applications that may include, but are not limited to, using the following approaches: econometrics, linear regression, multilevel/hierarchical linear modeling, Bayesian methods, propensity score matching, or data science (e.g., machine learning)
  • Writing researcher-oriented documents, including conference papers and presentations, academic journal articles, working papers, and technical documentation
  • Collaborating with and supervising analysts and programmers to implement statistical models for external partners and for internal research

Skills and Experience

  • Either a Ph.D. in Economics or related field; or a quantitative Ph.D. in Statistics, Public Policy, Sociology, Educational Psychology, Data Science, or a related statistically-focused field is required
  • 3+ years of post-doctoral research experience in economics, statistics, education, or a related field in an academic, non-profit, corporate, or other research-focused setting is preferred
  • Familiarity with the R programming language is preferred
  • Deep knowledge of statistical and analytic approaches for evaluating educational policies and programs

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