Sr Data Scientist

Sr Data Scientist Department: Data Science Team: Data Scientist Location: San Francisco, United States Type: Full-Time **About the Role** As a **Senior Data Scientist** on the Merchant Optimization team, you will play a pivotal role in identifying the optimal merchant selection for consumers and innovating on pricing models that enable merchants to effectively participate in the marketplace. Your work will directly shape Uber’s strategy by maximizing merchant ROI while driving growth and profitability across the Delivery business. You will leverage advanced experimentation, machine learning, and a deep understanding of marketplace dynamics to develop data-driven solutions that influence product direction and improve marketplace efficiency. The ideal candidate has strong technical expertise, a track record of driving impact through sophisticated analytical methods, and the ability to partner closely with product, engineering, and operations teams to bring scalable solutions to life. \-\-\-\- What You Will Do ---- 1. Lead and mentor a team of data scientists and applied scientists, fostering a culture of innovation and impact. 2. Design and execute rigorous A/B experiments to optimize pricing, incentives, and other marketplace levers. 3. Collaborate cross-functionally with engineering, product, and operations teams to drive strategic decision-making. 4. Generate actionable insights from large-scale data sets to inform both short-term execution and long-term product direction. 5. Define and measure key success metrics, ensuring alignment with business goals. 6. Advocate for best practices in data science, model monitoring, and causal inference within the organization. 7. Propose and guide framework of data analysis and experiments to drive business insight and facilitate decisions. 8. Collaborate closely with Engineering and Product teams to productionize models, enhance data observability and metrics with dashboards, and conduct experiments and in-depth analysis. 9. Communicate with leadership and cross-functional teams, including presentation of the Science team’s work on models