Staff Scientist - Reservations

Staff Scientist - Reservations Department: Data Science Team: Data Scientist Location: Seattle, United States Type: Full-Time **About the Role** The Reservations data science team owns the experience and algorithms powering the Uber Reserve Product in the Rider and Driver app. We optimize the user experience for both Riders and Drivers, matching, dispatch and pricing algorithms, as well as growth levers to deliver magical experiences and business value. The Reserve product is moving from a nascent mvp product to a more mature product, we have delivered on most of the “low hanging fruit” initiatives to improve the experience, building levers to customize the product and handle edge cases to consistently deliver high reliability. Currently, our focus is shifting towards driving efficiency to improve our unit economics and to drive adoption and growth. Some of the key projects involve major changes in Pricing, Matching and Dispatch that involve transitioning from heuristic based decision making to building machine learning models to make key decisions in real time, as well as important changes to Driver and Rider experience, including discoverability and awareness generation levers, and finally piloting new use cases that leverage the Reserve Tech as a platform to unlock new vectors of growth. **What You Will Do** 1. Deploy a wide variety of methodologies, including causal inference techniques, funnel analyses, and econometric modeling to identify our largest business opportunities. 2. Work together with Product, Operations, and Engineering partners to design a roadmap of features and initiatives as well as the long-term team strategy. 3. Run large scale experiments to validate the impact of new features. 4. Present findings to business and executive audiences \-\-\-\- Basic Qualifications ---- 1. Ph.D., M.S. or Bachelor's degree in Statistics, Economics, Mathemathics, Computer Science, Machine Learning, Operations Research, or other quantitative fields. 2. 6+ years of industry experience as an Applied or Data Scientist or equivalent. 3. Proficiency in programming languages (Python, Ja