Career Paths and Prospects in Academic Data Science: Report of the Moore-Sloan Data Science Environments Survey

SocArXiv, 2018

R. Stuart Geiger, Charlotte Mazel-Cabasse, Chihoko Cullens, Laura NoreĢn, Brittany Fiore-Gartland, Diya Das and Henry Brady. (2018). Career Paths and Prospects in Academic Data Science: Report of the Moore-Sloan Data Science Environments Survey. SocArXiv. osf.io/preprints/socarxiv/xe823

Abstract

This report is based on a 2016 survey of members and affiliates of three institutes of data science at major U.S. research universities, focusing on career paths for data scientists within academia. After considering how our respondents define data science, we identify various activities, priorities, resources, and concerns around data science in academia, especially with respect to data science careers. We end by providing recommendations about how universities can better support an emerging set of roles and responsibilities around data and computation within and across academic fields.