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.
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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.
