We’re changing the way people think about transportation. Not that long ago we were just an app to request premium black cars in a few metropolitan areas. Now we’re a part of the logistical fabric of more than 600 cities around the world. Whether it’s a ride, a sandwich, or a package, we use technology to give people what they want, when they want it.
For the people who drive with Uber, our app represents a flexible new way to earn money. For cities, we help strengthen local economies, improve access to transportation, and make streets safer.
And that’s just what we’re doing today. We’re thinking about the future, too. With teams working on autonomous trucking and self-driving cars, we’re in for the long haul. We’re reimagining how people and things move from one place to the next.
About the role
Are you interested in working at the intersection of applied quantitative research, engineering development, and data science? Do you have interest in developing and applying quantitative solutions related to Uber's uniquely challenging problems? If so, then this is the job for you.
About the team
Uber Everything Data Scientists embed with Uber's logistics delivery marketplace (for Everything!) and help resolve the most challenging quantitative problems related to Uber's expansive initiatives in the logistics space (such as UberEATS and UberRUSH). These fascinating and challenging problems include: demand prediction, menu recommendation, and supply chain optimization for UberEATS; batching, scheduling, routing algorithms for UberRUSH; dynamic pricing and supply positioning to improve logistics marketplace efficiency, and many more.
Since Uber Everything Data Scientists focus intently on the mathematics and engineering related to optimizing the economics and operations of Uber's logistics delivery marketplace, particular preference is given to candidates with backgrounds in Operations Research, Operations Management, Machine Learning, Statistics, or similar.
What you'll need
We are looking for people with advanced quantitative degrees (PhD preferred) who are comfortable enough with research methodologies that they can address abstract business and engineering problems with extreme precision, and who have the enthusiasm and initiative necessary to deliver those answers at Uber's fast pace. You should also have demonstrable programming skills (Python experience is even better) and be comfortable with engineering development process.