About the role
As a Staff Scientist working on Earner Program Logistics, you will solve high-stakes optimization and marketplace problems at the boundary of digital algorithms and physical-world delivery. Operating as a principal technical multiplier, you will shape the science strategy for core marketplace decisions-ensuring algorithms optimize for long-term platform value and are incentive-compatible.
In this role, you will lead the end-to-end scientific vision for complex logistics systems, partnering with teams across all of Uber to build a balanced, resilient, and highly efficient marketplace for eaters, merchants, and couriers globally.
What You’ll do
- Translate strategically important, unstructured problems into rigorous experiments and productionized solutions that move the needle for the Uber Eats business.
- Drive the end-to-end product development lifecycle from a science and data perspective, solving business challenges using Causal Inference and Optimization.
- Set the science strategy and experimentation standards across multiple teams, ensuring scientific rigor and driving organization-wide adoption of best practices.
- Act as a technical multiplier, identifying opportunities for better performance, efficiency, and reduction of technical debt in models and processes.
- Influence executive-level roadmaps by presenting complex technical findings and long-term strategic recommendations to senior leadership.
- Own the technical trajectory of critical product areas, ensuring solutions are designed to be extensible, modular, and observable while balancing short-term needs and long-term productivity.
Basic Qualifications
- Ph.D., M.S., or B.S. degree in Operations Research, Economics, Statistics, Applied Mathematics, or other quantitative fields.
- If M.S. degree, a minimum of 6+ years of industry experience required; if B.S. degree, a minimum of 8+ years of industry experience required.
- Deep expertise in statistical inference and experimental design (e.g., A/B, switchbacks, cluster-randomized trials).
- Proficiency in SQL and Python to work efficiently with large-scale datasets and distributed tools (e.g., Spark, Hive, Presto).
Preferred Qualifications
- Technical Vision: A track record of foreseeing architectural or scientific problems 12+ months out and addressing them before they impact the business.
- Impact & Scale: Experience leading multi-quarter, cross-functional initiatives that moved significant marketplace or financial metrics in production.
- Domain Mastery: Specialized expertise in Causal Inference at scale, Economics, or Marketplace Optimization.
For New York City, NY-based roles: The base salary range for this role is USD $216,000 per year - USD $240,000 per year.
You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.

