**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. **What You'll Need (Basic Qualifications)** - 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. **Preferred Qualifications** - 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. Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together. Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing [this form](https://forms.gle/aDWTk9k6xtMU25Y5A). Offices continue to be central to collaboration and Uber’s cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.