Advisory Board

Mitra Akhtari is a data scientist on the marketplace team at Airbnb, currently focusing on incorporating the marketplace lens into Airbnb's ranking algorithms. Over the last 5+ years, she has worked on a wide range of topics at Airbnb, ranging from measuring the impact of short-term rental regulations on the business to building internal data tools for measuring future value and standardizing tradeoffs. Her areas of expertise is using quasi-experimental methodology and observational data in solving causal inference problems. Mitra received her BA in applied mathematics and economics from UC Berkeley and her Ph.D. in economics from Harvard University, where she specialized in labor and public economics. 

Andrew Chamberlain is responsible for crafting the vision, strategy and product development for machine learning, algorithms, and personalization across Glassdoor’s full suite of consumer- and employer-facing products. Previously, he founded Glassdoor’s Economic Research group and served as Chief Economist for more than 6 years.  Andrew received his Ph.D. in Economics from the University of California, San Diego and his B.A. degrees in Economics and Business Administration from the University of Washington, Seattle.

Andrew has testified about his research before the U.S. Congress, and his work has been widely cited in academic research, a popular introductory economics textbook, and has been published in or featured by the Wall Street Journal, the New York Times, the Washington Post, the Los Angeles Times, The Economist, The Atlantic, USA Today, Reuters, and various academic journals.

Tom Cunningham is a senior staff data scientist at Twitter. Prior to joining Twitter, he worked at Facebook for five years as an economist and data scientist on the Economics faculty at Stockholm University and spent time as a visiting scholar at Harvard University, Tel Aviv University, and Caltech.  He received his Ph.D. in Economics from the London School of Economics.  He has worked on experimentation (shrinkage, multivariate shrinkage, cluster experimentation, two-sided network experimentation), content moderation (engagement-based signals of quality, quality-engagement tradeoffs), and company strategy (cross-app competition, tipping points), and conducts academic work on identifying implicit preferences in decision-making. 

Carolyn L. Evans is Chief Economist at Intel Corporation. Prior to joining Intel, Carolyn held the positions of Associate Professor of Economics at Santa Clara University, Senior Economist at the Board of Governors of the Federal Reserve, Senior Staff Economist for International Trade on the President’s Council of Economic Advisers, and Economist at the Federal Reserve Bank of New York. She has published academic articles and books in the areas of international trade, political economy, global macroeconomics, and corporate finance.

Carolyn holds a Ph.D. and M.A. in Economics and a B.A. in East Asian Languages and Civilizations, all from Harvard University.  She also holds a M.Sc.  from the London School of Economics. Carolyn is a member of the Conference of Business Economists, the Harvard University Discussion Group of Industrial Economists, the National Business Economics Issues Council, the National Association for Business Economics (NABE), and the American Economic Association. She serves on the Board of Directors of NABE, the Advisory Board for the MS in Business Analytics at Santa Clara University, and the Academic Advisory Board for the MS in Applied Economics at the University of San Francisco.

Daryl Fairweather is the chief economist of Redfin and a general partner at DITEC Ventures. Previously, she was a senior economist at Amazon working on problems related to employee engagement and managing a team of analysts. Daryl received her Bachelor's of Science from the Massachusetts Institute of Technology and received her Ph.D. and Master's degrees in economics from the University of Chicago where she specialized in behavioral economics. Daryl is currently writing the book Hate The Game to be published by the University of Chicago Press in 2024. 

Corrine Fusso leads the US Issuer Interchange team at Visa. Previously, she was an economist at Visa, where she developed a wide variety of insights that blend Visa data, 3rd party data, and proprietary research. Prior to Visa, she worked as a business intelligence analyst at Microsoft. Corrine received her master’s degree in economics from Claremont Graduate University and bachelor’s degrees in economics and international studies from the University of Washington in Seattle.

Celine Sun is Head of Data Science, Ads Core ML at Meta, where her team works on machine learning modeling to deliver personalized ads to Meta users. Previously she was Head of Data Science at Dropbox and Sr. Director of Data Science at Wealthfront. Celine specializes in applying economic/econometric theory to business problems and delivering scaled solutions. Celine received her Ph.D. in Financial Economics from the University of Washington.

Sean J. Taylor is co-founder and chief scientist at Motif Analytics. Previously he was a data scientist and manager at Lyft's Rideshare Labs and spent seven years as a research scientist on Facebook's Core Data Science team. Sean's work is at the intersection of experimentation and causal inference, with a focus on applied problems and generating business value using the latest methods. He earned his Ph.D. in Information Systems from NYU’s Stern School of Business as well as a BS in Economics from Wharton School.