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 computer science, but the ideal candidate would also have knowledge of, or interest in learning about, 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. 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.
Some recent achievements from our team include:
Candidates should have substantive experience (or demonstrate strong facility with) data science or data 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.
Full consideration will be given to applications received by March 24, 2019.
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.