Sendhil Mullainathan is the Roman Family University Professor of Computation and Behavioral Science at the University of Chicago Booth School of Business. His current research uses machine learning to understand complex problems in human behavior, social policy, and especially medicine, where computational techniques have the potential to uncover biomedical insights from large-scale health data. In past work he has combined insights from economics and behavioral science with causal inference tools—lab, field, and natural experiments—to study social problems such as discrimination and poverty. Prior to joining Booth, Mullainathan was the Robert C. Waggoner Professor of Economics at Harvard University, where he taught courses about machine learning and big data.

He began his academic career at the Massachusetts Institute of Technology. Mullainathan is a recipient of the MacArthur “Genius Grant,” has been designated a “Young Global Leader” by the World Economic Forum, was labeled a “Top 100 Thinker” by Foreign Policy Magazine, and was named to the “Smart List: 50 people who will change the world” by Wired Magazine (UK).

Josh Risley is the creator of Nightingale OS, our secure data repository and research computing platform. He leads software engineering, information security, and IT for Nightingale.

Previously, Josh was CIO and VP of Analytics and Engineering for Rush Street Gaming. Before that, he served as an FBI Special Agent, and before that, he was Director of Gaming Revenue Management for Caesars Entertainment.

Josh earned an Economics degree from Saint Louis University.

Nick Foster is a data integration analyst at Nightingale. Previously, he was a teaching assistant with the Northwestern Data Analytics and Visualization Boot Camp after graduating from the Metis Data Science Boot Camp. Before that, he worked with college students in a ministry setting for many years. Nick graduated with a BS in Physics from the University of Illinois Urbana-Champaign.

Nathan Juergens is a clinical consultant at Nightingale and a hospital medicine physician at the University of California, San Francisco.

He has a considerable background in research, having spent time at the NIH studying the epigenetics of addiction, working with the Kaiser Permanente Division of Research during his medical training, and completing an MPH at UC Berkeley. His recent work has focused on population health and the influence of technology on care delivery.

Jim assists portfolio projects prototype their data science solutions and helps  source grant and investment opportunities. Before Schmidt Futures, Jim was Head of Data Science at Lendable, where he built systems to automate due diligence processes and price portfolios of small loans in sub-Saharan Africa. He also worked at the Grattan Institute in Australia, where he focused on retirement savings policy, and at the Australian Treasury, on the ill-fated 2011 carbon price.

He's a Bayesian statistician, specializing in discrete choice, causal inference, time series analysis, and the incorporation of contemporary machine-learning methods into all three fields. Jim holds a Masters in Economics from the University of Melbourne, a first-class honours in Economics from La Trobe University, and was a 2014 Eric and Wendy Schmidt Data Science for Social Good fellow at the University of Chicago.