Principal Scientist - Marketplace

Principal Scientist - Marketplace Department: Data Science Team: Data Scientist Location: San Francisco, United States Type: Full-Time **About the Role** The Principal Scientist role supports **Uber Marketplace** by optimizing the engine that manages Driver Pricing and Incentives. This means building and deploying the economic models that balance driver earnings, marketplace efficiency, and rider affordability in real-time across thousands of cities globally. The work involves deep causal inference, machine learning on massive, real-world datasets, and owning the core principles that define a healthy, liquid marketplace where you **move the real world** at enormous scale. Success in this role requires not only generational technical depth but also the ability to drive high-stakes alignment on ambiguous problems with Director and VP-level leaders in Product, Engineering, and Operations. You will navigate constant trade-offs between short-term growth and long-term marketplace sustainability, demanding a deep **trip obsessed** mindset to simplify immense complexity. If you are ready to set the technical direction for one of Uber's most critical and high-impact product areas, this is where you will grow with the challenge. **What You’ll Do** - **Define** the long-term science roadmap for Driver Pricing, matching, and Incentives, translating ambiguous business problems into rigorous, implementable economic and machine learning solutions that drive step-change improvements. - **Design** and lead the implementation of complex causal inference and large-scale experimentation (A/B testing) frameworks to measure the true, long-term impact of pricing and incentive policy changes on both driver behavior and overall marketplace health. - **Drive** excellence and rigor in science methodologies, leveraging techniques such as machine learning, experimentation, causal inference, time series analysis, and natural language processing to address complex marketplace challenges. - **Build** critical, cross-functional alignment with senior Product, Engineering, and Operations leaders, using deep data-driven narrativ