Optimizing the Three-Sided Marketplace of Uber Eats

12/3/18 | 4:00pm | E51-335


 

 

 

 

Dr. Chen Peng

Head of Data Science
Uber Eats 

and

Dr. Robby Zeller

Tech Lead Manager for the Courier Pricing
Uber Eats 


Abstract:

Uber is a company connecting virtual bits with physical atoms; Uber Eats extends the mission of Uber beyond human transportation---it creates a uniquely complex and efficient three-sided marketplace that brings atoms (in this case, food) to millions of customers. Launched three years ago, Uber Eats is now operating in more than 350 cities globally and growing even faster than Uber’s ride-sharing business.

The Uber Eats data science team develops state-of-the-art machine learning, optimization, and economics models that power the product and business of Eats. Examples include the personalized ranking and recommender systems for restaurants and menu items, meal preparation time and delivery time prediction models, demand & supply forecasting, dynamic pricing, network optimization, and many more. 

At this event, speakers from Uber Eats will give an overview of the Uber Eats data science team, talk about some of the challenging and fun projects they are working on---with a deep-dive into the incentives optimization system that helps improve courier positioning to balance demand and supply on their network. They will also discuss some exciting full-time and internship opportunities for graduate students from various domains.

Bio: Chen Peng is the Head of Data Science for Uber Eats. His team of 40+ data scientists work on both model & algorithm development as well as product analytics to improve the growth, efficiency and reliability of Uber Eats’ three-sided marketplace. Example projects include personalized restaurant and dish recommendation, delivery time prediction, demand & supply forecasting, dynamic pricing, dispatch and routing optimization, etc. Prior to Uber, Chen worked as a data scientist at Google, building mathematical models to optimize capacity and resource allocation for Google’s global Cloud platform. He received his PhD in Management Science & Engineering from Stanford in 2011 and a BS in Information Technology from Zhejiang University, China in 2007.

Bio: Robby Zeller is a Tech Lead Manager for the Courier Pricing space on the Uber Eats data science team. His team develops the models and optimization algorithms that determine the prices that are paid to delivery partners on the Eats platform, from structural pricing to weekly positioning incentives to real-time surge pricing. Prior to Uber, Robby worked in the aerospace industry, analyzing the fluid dynamics in propellant and pneumatic systems on space launch vehicles. He received a PhD and MS in Environmental Fluid Mechanics from Stanford and a BA in Environmental Engineering from UC Berkeley. 

Event Time: 

2018 - 16:00