Helin Zhu

About Helin Zhu

Maps team provides the backbone of Uber’s service, from the driver and rider experience and display to the route recommendations and travel time predictions from one point to another. These routes and predictions feed into all of Uber’s decision systems, like dispatch, UberPool matching, and pricing. Our turn-by-turn navigation service allows drivers to effectively navigate while on or off trip, while our geosearch engine allows users to search for a destination or pickup point. To power these services, Uber Maps also generates base map data (the road map definition and features) and point of interest data (such as restaurants or hotels). A sister team, Sensing and Perception, provides location estimates for Uber’s users while they are engaging with the app; these location estimates also power the user experience and decision systems. Sensing and Perception also does sensor inference modeling to support a wide variety of products, such as accident or fraud detection. Our teams play a critical role in providing a smooth and comfortable rider and driver experience on Uber’s platform, from the moment they open the app until the moment they arrive at their destination. We’re looking for data scientists to contribute to all aspects of Uber Maps. We seek candidates with strong background in Statistics, Experimental Design, Machine Learning and Operations Research, etc.

Experience

1. Senior Manager, Head of Maps Applied & Data Science

   Uber

   Aug 2021 — Present · San Francisco, CA, US

   I lead the Maps Science team, consisting of 20+ applied scientists (AS), data scientists (DS), and several managers. My team is responsible for solving some of the largest, most challenging modeling problems in Uber, including travel time prediction (ETA), traffic prediction, route recommendation, navigation, search & ranking, pickup & dropoff recommendation, personalization, location intelligence, trip intelligence, etc. We achieve this by developing a diverse combination of statistical, machine & deep learning, and optimization models. The outputs of these models power the core trip flow experience for all products in the Rides & Eats businesses, and core internal decision systems such as pricing and matching.

Education

• Nanjing University

  Bachelor of Science (BS), Mathematics

  2007 — 2011

• Georgia Institute of Technology

  Doctor of Philosophy (PhD), Operations Research

  2011 — 2016

Skills

• Matlab
• Sql
• C++
• Python
• Java
• Sas
• R