Presented By
O’Reilly + Cloudera
Make Data Work
March 25-28, 2019
San Francisco, CA
Ying Yau

Ying Yau
Distinguished Data Scientist, Walmart Labs

Jeffrey Yau is a distinguished data scientist at WalmartLabs, where he leads data science for the store technology department. Previously, he was the chief data scientist at AllianceBernstein, a global asset-management firm; the vice president and head of data science at Silicon Valley Data Science, where he led a team of PhD data scientists helping companies transform their businesses using advanced data science techniques and emerging technology; the head of risk analytics at Charles Schwab; director of financial risk management consulting at KPMG; assistant director at Moody’s Analytics; and assistant professor of economics at Virginia Tech. Jeffrey’s active in the data science community and often speaks at data science conferences and local events. He has many years of experience in applying a wide range of econometric and machine learning techniques to create analytic solutions for financial institutions, businesses, and policy institutions. Jeffrey holds a PhD and an MA in economics from the University of Pennsylvania and a BS in mathematics and economics from UCLA.


4:20pm5:00pm Wednesday, March 27, 2019
Ying Yau (Walmart Labs)
Average rating: ***..
(3.29, 7 ratings)
Time series forecasting techniques are applied in a wide range of scientific disciplines, business scenarios, and policy settings. Jeffrey Yau discusses the applications of statistical time series models, such as ARIMA, VAR, and regime-switching models, and machine learning models, such as random forest and neural network-based models, to forecasting problems. Read more.