Senior Scientist, Delivery Courier Pricing

About the Team

The Uber Eats Marketplace team is the heart of the Uber Eats business. We build the platform and products that power the magical experience of connecting eaters, couriers, and restaurants. As a critical component of this ecosystem, the Courier Pricing team is responsible for the complex systems that determine courier earnings on every Uber Eats delivery worldwide.

Our mission is to build and refine a fully automated pricing system that optimizes our three-sided marketplace for consumers, couriers, and merchants. We leverage sophisticated optimization, machine learning, and causal inference techniques to balance efficiency, reliability, and cost under highly dynamic conditions. This is a high-impact team solving core business challenges across diverse verticals-including restaurant delivery, grocery, and retail-and supporting global markets with unique and complex problems.

What You'll Do

• Own the end-to-end lifecycle of scientific models and algorithms, from ideation and development to deployment and iteration, tackling our most complex pricing challenges.
• Act as a thought leader, influencing the product and technical roadmap by identifying new opportunities and translating them into actionable scientific projects.
• Lead the design and analysis of large-scale experiments, pushing the boundaries of causal inference to measure the impact of our pricing strategies and deliver actionable insights.
• Drive collaboration with senior stakeholders across Product, Engineering, and Operations, effectively communicating complex findings and presenting strategic recommendations to leadership.
• Mentor and guide junior scientists on the team, elevating the overall technical bar and fostering a culture of scientific rigor.

• A Ph.D. in a quantitative field (e.g., Statistics, Economics, Computer Science, Operations Research) with 2+ years of industry experience, OR a Master's/Bachelor's degree in a similar field with 5+ years of relevant industry experience.
• Deep, hands-on expertise and a proven track record of applying advanced methods from machine learning, statistics, optimization, and causal inference to solve complex, real-world business problems.
• Proven experience leading complex, cross-functional projects, with a track record of influencing the technical direction and output of the team.
• Proficiency in modeling, data analysis, and programming using a language like Python or R.
• Experience querying databases using SQL.
• Excellent communication and presentation skills, with the ability to influence both technical and non-technical audiences.

• Expert-level knowledge in one or more of the following areas: experimental design, causal inference, machine learning, economics, or optimization, with a track record of designing and implementing model architectures and algorithms.
• Direct experience in a marketplace-related problem space, especially pricing optimization.
• Proven ability to design and analyze large-scale experiments to inform critical pricing and product decisions.
• Experience working with large datasets using distributed computing systems like Spark, Hive, or Presto.