Senior Data Science Manager — Pricing & Experiments

Uber; San Francisco (CA); On-site; USD 216,000 - 240,000; Full time

Benefits offered by this job

Bonus program

Equity award

401(k) plan

Benefits

Job summary

Uber’s Eats Marketplace team seeks a senior data scientist to lead a team focused on pricing and incentives, building automated systems with optimization, ML, and causal inference. You will own end-to-end product development from data to deployment and collaborate with product and leadership to define success metrics.

This role emphasizes mentoring, cross-functional collaboration, and translating business needs into technical roadmaps across multiple product areas.

Qualifications

• PhD, MS, or BS in Economics, Statistics, ML, OR, or other quantitative fields.
• 7+ years of industry experience as an Applied or Data Scientist or equivalent (or 4+ years with PhD).
• 1+ years managing a team of scientists.
• Excellent communication and collaboration skills to lead across product areas.

Responsibilities

• Lead a team of Scientists, including growing and mentoring team members.
• Partner with cross-functional stakeholders to identify business needs and translate them into technical roadmaps.
• Communicate complex findings to senior leadership.
• Solve ambiguous business problems using data-driven approaches including Causal Inference, Optimization, and ML.
• Own the product development cycle end-to-end from data and modeling aspects.
• Define metrics in collaboration with cross-functional partners.

Skills

Team leadership

Causal inference

Optimization

ML modeling

Python/R/Scala

Communication

Education

PhD/MS/BS in a quantitative field

Tools

Spark

SQL

Job description

Uber’s Eats Marketplace team seeks a senior data scientist to lead a team focused on pricing and incentives, building automated systems with optimization, ML, and causal inference. You will own end-to-end product development from data to deployment and collaborate with product and leadership to define success metrics.

This role emphasizes mentoring, cross-functional collaboration, and translating business needs into technical roadmaps across multiple product areas.