Senior Product Manager, Earner Intelligence

Senior Product Manager, Earner Intelligence Department: Product Team: Product Management Location: San Francisco, United States Type: Full-Time **About the Role** Are you an experienced Machine Learning Product Manager who likes to ship products to end users? Are you looking to build impactful ML products, platforms, and pioneer innovation within Uber? If so, this role might be for you. You will identify and work on key opportunities to bring more growth and efficiency, leveraging our wealth of data and different ML techniques, while spearheading innovation and building platforms to scale the impact to more use cases. This requires judgment to make difficult trade-offs, blending ML with user experience, and the ability to build simplicity from complexity. In this role, you will build ML products to power user-facing solutions, and also develop platform tools that are used across teams, with a primary focus on Earners - drivers and couriers. **About the team** We are the Earner Intelligence team, focused on creating ML solutions and platforms to drive and scale efficient growth. We build products to tailor the product experience throughout the earner lifecycle from user acquisition, to conversion, early lifecycle, and retention, while also working with other (“domain”) teams to ship solutions and to scale to more use cases. The team employs a variety of ML/AI techniques, spanning from causal ML, supervised ML, multi-armed bandits, genAI LLM to deep learning embeddings to build impactful products. Our goal is to make sure that the earner journey is great at every touch point, that we build trust with Earners, and that we drive efficient growth to Uber’s core business and its strategic bets. **What the Candidate Will Need / Bonus Points** \-\-\-\- What the Candidate Will Do ---- 01. Own the product roadmap and lead vision, definition, and execution for building Uber’s strategy on efficient growth and user experience optimization using ML. 02. The team employs a variety of ML/AI techniques, spanning from causal ML meta learners, supervised ML, RL multi-armed bandits, genAI LLM to deep learning embeddi