Staff Scientist, Marketplace (Multiple Teams)

Staff Scientist, Marketplace (Multiple Teams) Department: Data Science Team: Data Scientist Location: San Francisco, United States Type: Full-Time **About the Role** End-to-end product development from a data, analytics, modeling and experimentation perspective. Specifically, formulating ambiguous business problems, prototyping various machine learning & optimization & causal inference & marketplace dynamics models, producing data insights, and designing & analyzing experiments. #### **About the Team\*\*(We are hiring for multiple teams)\*\*** We are building the future of Uber's mobility and logistics platforms. Our teams drive innovation across critical areas, including: - **Delivery Marketplace**: A central pillar of Uber’s delivery products, serving as the "brain" of the operation. We drive every decision that enables orders to go from point A to point B — from Uber Eats & Grocery, to newer verticals like Uber Direct and Connect. We’re responsible for running an efficient marketplace with dispatch & pricing decisions. - **Maps**: Building the geospatial technologies for all of Uber, including travel time prediction (ETA), routing, search & ranking, pickup & dropoff recommendation, and trip intelligence. The outputs power marketplace systems like pricing & matching and the core trip experience. - **Uber One Membership**: Enhancing user experience and growth for Uber One, a fast-growing program providing members with exclusive benefits, best prices, and priority across the platform. - **Experimentation Platform**: Building the experimentation platform and the underlying measurement models at Uber, providing reliable, trustworthy and agile experimentation and experiment analysis to power business decisions across the entire Uber ecosystem. - **Autonomous Mobility & Delivery (AM&D)**: Pioneering the integration of autonomous vehicles into the existing ecosystem, tackling the complex challenge of building a reliable, efficient, and scalable hybrid marketplace for both Rides and Eats. **What You’ll Do** - Solve ambiguous, challenging business problems using data-driven approaches including Causal Inference