Staff Scientist, Tech - Science

Job-:
Science

Location:

San Francisco, CA, United States;
Seattle, WA, United States;
New York City, NY, United States;
Sunnyvale, CA, United States

Schedule:

Full time, Level 5BPosted:
About the Role and Team As a Staff Scientist at Uber, you will solve the complex, global-scale puzzle of how millions of people and things move in the real world. Operating as a technical multiplier at the high-stakes intersection of digital systems and physical movement, you will navigate extreme ambiguity, set scientific strategy, and make critical decisions with imperfect information.

Whether you are architecting next-generation marketplace mechanisms or defining experimentation guardrails, you will thrive in an environment where high performance and massive scale are inextricably linked.

You will join the Rider Pricing and Incentive team, which owns the real-time algorithms powering our mobility business. In this role, you will define the scientific strategy for measuring marketplace performance and optimizing complex pricing systems. Beyond building models, you will develop data insights to identify high-impact opportunities and influence executive roadmaps. You will also drive execution by providing technical guidance to junior scientists and partnering cross-functionally with Product and Engineering teams to deliver high-impact, productionized results.

What You’ll DoSet Scientific Vision:
Define the 1–2 year scientific strategy and technical roadmap for real-time rider pricing, identifying high-impact opportunities.  Lead the Architecture and Design:
Define the scientific frameworks and next-generation pricing algorithms that ensure our models are modular, extensible, and observable at global scale.

Act as a Technical Multiplier:
Elevate team-wide technical execution by identifying opportunities for system efficiency, model performance, and reduction of technical debt across software and science pipelines.

Influence Senior Leadership:
Partner directly with Product, Engineering, and Business Executives, translating complex data and technical findings into clear strategic recommendations.

Own Technical Trajectory:
Direct the evolution of critical pricing systems, balancing short-term needs with long-term scalability and efficiency.

Establish Scientific Guardrails:
Set experimentation standards and statistical frameworks across multiple teams, driving organization-wide adoption of best practices in causal inference and marketplace testing.

Basic Qualifications Ph.D., M.S., or B.S. in Economics, Operations Research, Statistics, Computer Science, Applied Mathematics, or related quantitative fields.

Minimum of 6+ years (M.S./Ph.D.) or 8+ years (B.S.) of industry experience building, deploying, and scaling quantitative models in production environments.

Deep expertise in statistical inference, advanced experimental design (e.g., switchbacks, cluster-randomized trials), and quantitative economic modeling.

Proficiency in SQL and Python working with large-scale distributed data tools (e.g., Spark, Presto).

Preferred Qualifications Domain Mastery:
Recognized expertise in marketplace design, pricing algorithms, industrial organization, ML system design, or large-scale optimization in high-throughput environments.

Technical Vision:
Proven track record of anticipating scientific or system bottlenecks 12+ months in advance and building foundational frameworks to address them.

Cross-Functional Leadership:
Demonstrated success leading multi-quarter, org-wide initiatives that moved major marketplace or financial metrics in production.

Executive Impact:
Ability to synthesize complex statistical or economic insights into compelling strategic narratives for senior leadership.

Responsibilities For New York City, NY-based roles:
The…