The Golub Capital Social Impact Lab (GC Lab) has a 2-year post-doctoral fellowship opening working with The Economics of Technology Professor Susan Athey and other faculty affiliates of the GC Lab to responsibly and equitably use technology to improve people’s lives at scale.
The GC Lab aims to increase the effectiveness of social impact organizations through the use of digital technology, particularly in the domains of education, charitable giving, health, government services, workers and career transitions, and financial health. We collaborate with a broad range of non-profit, non-governmental, and for-profit organizations to research and achieve social impact goals. The GC Lab is housed in the Graduate School of Business (GSB) at Stanford University and contributes to the Business and Beneficial Technology pillar of the Business, Government, and Society Initiative therein.
We are seeking to hire an applied statistician with a background in econometrics or causal inference, preferably with a focus on economics or other social science applications. The ideal candidate will have a strong computational and data science background, and an interest in social science research to improve people’s lives through beneficial technology. Excellent candidates with other specialties or backgrounds related to the lab’s work will also be considered.
There are a number of projects to which the postdoctoral fellow may be matched based on interest, most of which involve collaborating with a social impact team or organization in the tech sector. The projects span the domains of education, labor, and personal finance. Examples of our related research include developing new methods for modeling worker transitions through their career to better understand the gender wage gap, developing recommendation systems for educational applications, or writing personalized stories in an English-language learning app for children.
The position involves:
The ideal candidate is either preparing for an academic position in a field closely aligned with the lab, for which collaboration on the lab’s projects would serve as strong preparation, or an industry position, (i.e., in a technology company). This position does not incorporate independent research by the fellow outside the scope of the lab; any independent research would be conducted outside of regular work hours and should be managed so as to not present a conflict of commitment to the lab.
Depending on the fellow’s skills and interests, the fellowship will allow the opportunity to: use and develop cutting-edge methodology for working with large data sets, using university infrastructure or the infrastructure of tech firms, including tools of machine learning and causal inference; develop expertise in managing large-scale empirical projects with large code bases written by teams; create novel experimental designs, including adaptive and dynamic treatment regimes, bandits, and contextual bandits; run experiments in collaboration with technology firms or on tech firm platforms; and/or develop coding expertise for publicly released software.
The postdoc will be responsible for:
The strongest applicants will have a variety of skills and preparation, and a strong desire to rapidly fill any skills and experience gaps. Desirable skills and experience include:
To apply, please complete the application here, including a CV, cover letter, 3 references, and job market/other paper. Please send any questions to Director Kristine Koutout at kkoutout@stanford.edu. Applications will be accepted on a rolling basis.
In your cover letter, answer the following questions: