Sr. Scientist - Mobility Matching

About the Role

Have you ever wondered why it's taking so long for an earner to be matched to your trip, why the ETA is so long, or how an Earner is picked from the many around you? If so, the Mobility Matching Science team is for you!

The Matching team at Uber builds the systems that determine the optimal way to fulfill trips on the Mobility platform. We work on the problems of determining which earners to send an offer to and when. The solutions we build are critical for maintaining reliability and ensuring the trust of riders and earners alike.

We are looking for experienced scientists who relish the opportunity to develop novel approaches and apply them at Uber's scale. They ideally have a good balance of causal inference, analysis, experimentation, and modeling knowledge, as well as, an ability to use these skills to identify business opportunities and deliver product recommendations.

What You'll Do

• Develop data-driven business insights and work with cross-functional stakeholders to identify opportunities and recommend prioritization of product, growth and optimization initiatives
• Design and analyze experiments, communicating results that draw detailed and actionable conclusions
• Analyze and contribute to development of optimization algos and ML models for use in mobility matching
• Collaborate with cross-functional teams such as product, engineering and operations to drive system development end-to-end from conceptualization to final product

Basic Qualifications

• Ph.D. in Statistics, Economics, Machine Learning, Operations Research, Computer Science, or another quantitative field.
• Minimum 2 years of industry experience as an Applied Scientist, Data Scientist, or in a similar quantitative role.
• Strong knowledge of the mathematical foundations of statistics, machine learning, optimization, and economics.
• Proven experience in experimental design (e.g., A/B testing) and causal inference.
• Proficiency in using Python or R for data analysis, modeling, and algorithm prototyping at scale with large datasets.
• Experience with exploratory data analysis, statistical analysis and testing, and model development.

Preferred Qualifications

• Ph.D., or M.S. in Statistics, Economics, Machine Learning, Operations Research, Computer Science, or another quantitative field.
• Minimum 5 years of industry experience as an Applied Scientist, Data Scientist, or in a similar quantitative role.
• Strong knowledge of the mathematical foundations of statistics, machine learning, optimization, and economics.
• Proven experience in experimental design (e.g., A/B testing) and causal inference.
• Proficiency in using Python or R for data analysis, modeling, and algorithm prototyping at scale with large datasets.
Experience with exploratory data analysis, statistical analysis and testing, and model development.

For San Francisco, CA-based roles: The base salary range for this role is USD$190,000 per year - USD$211,000 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. More details can be found at the following link https://jobs.uber.com/en/benefits.