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The Stanford Computational Policy Lab (SCPL) seeks multiple data scientists and software engineers to help craft technical solutions to tough policy problems. Our work is grounded in statistics, machine learning, and software engineering, but the ideal candidate would also have interest in a wide range of fields: from law, to policy, to criminal justice, to education. Our positions are tailored to each individual’s strengths; your exact duties will depend on what skills you bring to the lab, and what you want to learn here. You should have—above all else—a desire to develop technical tools and interventions to address some of today’s thorniest policy issues.

SCPL is an interdisciplinary group of researchers, practitioners, and engineers that uses technology to address pressing issues in criminal justice, education, voting rights, and beyond. SCPL harnesses advances in data science to study the impact of policy choices at unprecedented scales, and builds algorithmic tools to guide high-stakes decisions. By bringing a computational perspective to public policy, SCPL improves the lives of millions of people—especially those affected by inefficient and unfair systems and practices.

Data scientists and engineers on our team have a lot of freedom: they determine requirements on their own and have the opportunity to plan and execute their own long-running projects. Our data scientists use a wide range of statistical techniques to derive insight from data—from multi-level regression, to Bayesian inference, to multi-armed bandits, to natural language processing. Similarly, our software engineers have built anything from complicated data engineering pipelines to full-stack web platforms. Learning is a core part of our experience in the lab. If you’re not familiar with these techniques, you will have plenty of opportunities to learn them—and many more.

Some recent achievements from our team include:

  • standardizing and publishing records for 250 million police stops from 80 American cities and states;
  • constructing the first race-blind case charging platform for any American district attorney;
  • working with a major American city to reduce racially disparate traffic stops;
  • quantifying, for the first time, the relative dearth of double voting in presidential elections by analyzing over 100 million voter records; and
  • building a chatbot to interactively teach high school students algebra.

Candidates should have substantive experience (or demonstrate strong facility with) data science or software engineering. None of your experience needs to be in technical policy interventions, but a background working in government, advocacy, and/or in a criminal justice context is a plus. Applicants should have, at a minimum, a bachelor’s degree. Master’s or PhD graduates are encouraged to apply as well.

We highly encourage applications from all backgrounds, including, but not limited to: people of color, people from working class backgrounds, women, and LGBTQ people. We believe that the most impactful work—and the best work environments—include and foster a range of diverse perspectives.

Apply now!

Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.