15 November 2018
Uber Eats works with over 160,000 restaurants in 350 markets in 35 countries across 6 continents to deliver your favorite foods fast - averaging 31-minutes global delivery time. Our massive scale and global presence bring unique and challenging data science challenges. With great problems come the need for top talent, diverse perspectives, and an appetite for challenging the food delivery status quo.
This event is about celebrating and sharing some of the work done by data scientists and engineers on the Uber Eats team. Attendees will learn about how we apply data science and data modeling to ensure the health and efficiency of Uber Eats' three-sided marketplace. In addition, the event will feature discussion and Q&A that will give audience members a firsthand look at what it's like to work in one of the largest data science organizations in the industry on some of the field’s most interesting challenges.
How does Uber Eats determine the best way to deliver your food? What makes a good delivery? The Uber Eats Logistics Data Science team creates algorithms to balance the often competing interests of the eater, courier, and restaurant when getting the food to your door. Learn their fundamental optimization and machine learning challenges and how they're thinking about solving them.
Developing algorithms for a dynamic, highly-interconnected marketplace presents a unique set of both data science and engineering challenges. We dive deeper into some of these challenges and describe how we address them using the Eats Marketplace Simulator.
Close to the BDFM, 123 & NQR
Or better yet, take an Uber!
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