Staff Scientist: Real-Time Pricing & ML Systems

Uber; United States; Hybrid; USD 216,000 - 240,000; Full time

Benefits offered by this job

Bonuses

Equity

401(k) plan

Benefits

Job summary

Uber seeks a Staff Scientist to define the scientific strategy for real-time rider pricing and to guide architecture for scalable pricing systems. You will partner with Product, Engineering, and Business Executives to translate data insights into strategic recommendations and drive production-ready results.

You will mentor junior scientists and own the technical trajectory of pricing systems, establishing guardrails for experimentation and causal inference across multiple teams.

Qualifications

• Ph.D., M.S., or B.S. in Economics, Operations Research, Statistics, Computer Science, Applied Mathematics, or related quantitative fields.
• 6+ years (M.S./Ph.D.) or 8+ years (B.S.) of industry experience building, deploying, and scaling quantitative models in production environments.
• Proficiency in statistical inference and advanced experimental design, plus quantitative economic modeling.

Responsibilities

• Define the 1–2 year scientific strategy and roadmap for real-time rider pricing.
• Define frameworks and pricing algorithms for modular, scalable models at global scale.
• Mentor junior scientists and partner with Product and Engineering to deliver productionized results.
• Translate data findings into strategic recommendations for senior leadership.
• Direct the evolution of pricing systems balancing short-term needs with long-term scalability.
• Set experimentation standards and causal inference frameworks across teams.

Skills

Statistical inference

Experimental design

Quantitative modeling

SQL

Python

Education

Ph.D./M.S./B.S. in Economics/OR/Statistics/CS/Applied Mathematics

Tools

Spark

Presto

Job description

Uber seeks a Staff Scientist to define the scientific strategy for real-time rider pricing and to guide architecture for scalable pricing systems. You will partner with Product, Engineering, and Business Executives to translate data insights into strategic recommendations and drive production-ready results.

You will mentor junior scientists and own the technical trajectory of pricing systems, establishing guardrails for experimentation and causal inference across multiple teams.