Uber
Manager II, Science, Tech - Science
$216K–$240K
San Francisco, California +1 · Manager · Full-time · Posted Sep 17, 2026
- Location
- San Francisco, California
New York City, New York - Experience
- 7+ years of industry experience as an Applied or Data Scientist or equivalent, or 4+ years with a Ph.D.; 1+ years managing a team of scientists.
- Education
- Ph.D., M.S. or Bachelor's degree in Economics, Statistics, Machine Learning, Operations Research, or other quantitative fields.
About the job
Leads a science team developing data-driven pricing and incentive solutions for Uber Eats’ global marketplace, from problem definition and modeling through experimentation and product delivery.
What you'll do
- Lead, grow, and mentor a team of scientists; collaborate with stakeholders to translate business needs into technical roadmaps.
- Solve business problems using causal inference, optimization, and machine learning, and own product development from data and modeling through delivery.
- Define success metrics, design and analyze experiments, and communicate findings and recommendations to senior leadership.
What they ask for
- Degree in Economics, Statistics, Machine Learning, Operations Research, or another quantitative field.
- 7+ years of industry experience as an Applied or Data Scientist or equivalent, or 4+ years with a Ph.D.
- 1+ years managing a team of scientists.
- Programming experience in at least one language and experience designing experiments and interpreting results.
Nice to have
- Ph.D. in a quantitative field; 2+ years managing scientists.
- Experience in large-scale marketplace algorithm design or experimentation platforms, or leading technical projects from concept to production.
Pay
USD $216,000 per year - USD $240,000 per year (base salary, New York City); USD $216,000 per year - USD $240,000 per year (base salary, San Francisco)
Tools
Python, R, Scala/Spark
AI focus
Uses machine learning, optimization, and causal inference to develop automated pricing and incentive systems for a three-sided marketplace.
Model-written summary · the original posting is authoritative