David Reiley

David Reiley is an Adjunct Professor at the UC Berkeley School of Information, where he teaches Data Science 241: Experiments and Causal Inference. He is also a Distinguished Scientist at SiriusXM Pandora, where he has worked since 2020, focusing on research related to advertising and consumer behavior.

Dr. Reiley received his Ph.D. in Economics from MIT in 1996 and his AB in Astrophysical Sciences from Princeton University in 1991. His academic career includes positions as Arizona Public Service Professor of Economics at the University of Arizona (2006-2009), Associate Professor of Economics at the University of Arizona (2001-2006), and Assistant Professor of Economics at Vanderbilt University (1996-2001). He has also held visiting positions at institutions including Northwestern University, the European University Institute, and the Kiev School of Economics.

Dr. Reiley is a leading expert in field experiments in economics, having helped popularize their use in the discipline. His research focuses on advertising effectiveness, auction theory, charitable giving, and electronic commerce. He has conducted numerous field experiments to measure the effects of online advertising, particularly during his time at Yahoo! Research (2007-2012) and Google (2012-2015). His work has demonstrated how field experiments can provide valuable insights into consumer behavior that traditional observational methods cannot capture.

Dr. Reiley has received several prestigious awards including the Distinguished Faculty Award from UC Berkeley School of Information (2016) and the Dick Wittink Prize for the best paper published in Quantitative Marketing and Economics (2015). He was also honored with Yahoo!'s Super Star Award, the company's highest honor for employees, in 2009.

As an educator, Dr. Reiley has been instrumental in developing courses on field experiments and experimental methods. He has advised numerous students and collaborated with researchers across various institutions. His textbook "Games of Strategy" (co-authored with Avinash Dixit and Susan Skeath) is widely used in game theory courses.