Yuri is a Member of Technical Staff / Data Scientist at eBay in New York City. He is currently focused on developing scalable machine learning algorithms to produce high quality item recommendations. Yuri holds a Ph.D. degree from the Applied Physics and Applied Mathematics department from Columbia University and an undergraduate degree in Physics from UC Berkeley.
Innovations in Recommender Systems for a Semi-structured Marketplace:
eBay has over 1 billion live items on the site at any given time. The lack of structured information about listings as well as variable inventory makes traditional collaborative filtering algorithms difficult to use in eBay’s large semi-structured marketplace. We will discuss approaches to overcome these challenges using machine learning and deep learning (both text and image based models). The details of the sampling strategy, feature engineering, and machine learned ranking model are all important for delivering improved operational metrics in A/B tests. We will cover both system architecture engineering as well as data science and machine learning methods that were developed to generate high quality recommendations.