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Data Scientist - Marketplace Optimization






San Francisco, CA, US


At Uber, we ignite opportunity by setting the world in motion. We take on big problems to help drivers, riders, delivery partners, and eaters get moving in more than 600 cities around the world.


We welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. If you have the curiosity, passion, and collaborative spirit, work with us, and let’s move the world forward, together.

About the role


In Marketplace you’ll be at at the center of Uber’s business, where riders and drivers come together at extraordinary scale. As a data scientist, you’ll combine clear product vision, deep technical skills and powerful data analysis to improve the algorithms that run Uber’s vast worldwide marketplace every minute of the day. We’re looking for you to produce elegant solutions that are practical, effective and can work at Uber scale.


Our team tackles problems such as optimizing Uber’s short and long term pricing systems; efficiently matching incoming trip requests in Uber’s dispatch system; developing innovative incentive schemes that reward riders and drivers for choosing our network; and providing optimal routes and accurate turn-by-turn navigation to save time for everybody. We also forecast, monitor and evaluate all aspects of our marketplace using both large scale observational data and thoughtful experimentation.

If you are passionate about original ideas, and take pride in seeing those thoughts come to life in a high impact setting, then you’ll be at home in our team where creative exploration and iterative experimentation are at the heart of what we do. As part of Marketplace, you will work side-by-side with Uber's engineering team to scale your ideas across Uber's real-time production systems, and then strive to gain insights from the real world outcomes we see.

What we’re looking for


Our team attracts people from a wide range of backgrounds, from areas with a focus on empirical modeling (Machine Learning and Statistics), to those that emphasize marketplace efficiency (Economics, Operations Research and Operations Management), to those with a tradition of utilizing rich geospatial data to better understand mobility (Transportation Engineering). We also highly value candidates from a Computer Science background who have a strong interest in these problem spaces.


We love hearing from talented applicants who are enthusiastic about tackling our business problems. Here are some guidelines for what we look for in a candidate:


  • Strong quantitative background. MS or PhD preferred, but waived for candidates with considerable practical work experience in data science or engineering out of school.

  • Ability to think creatively and insightfully. We’ve got plenty of hard problems and nowhere to look up the answers.

  • Data-driven perspective. The truth is out there: we just need to measure it.

  • Open mindedness. We favor flexibility in our technical approaches and value the ability to see things from a driver or rider’s perspective.

  • End-to-end ownership. You’ll dive into the data to understand the whole context, passionately advocate for your ideas, help out with implementation where needed, and always take responsibility for ensuring that riders and drivers have a great experience on our network.

  • Familiarity with common technical tools for data analysis - Python (with Pandas, etc.), R, SQL a plus


  • Programming chops. A solid understanding of algorithms and data structures. Python skills and/or experience in developing high performance production quality code in C, C++, Java, etc a plus.

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