Manager II, Science, Tech - Science

Uber

United States

On-site

USD 216,000 - 240,000

Full time

5 days ago
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Benefits offered by this job

Bonus program
Equity awards
401(k) plan
Comprehensive benefits

Job summary

Uber is seeking a Senior Data Scientist to join the Uber Eats Pricing and Incentives team, focusing on end-to-end product development from data, analytics, modeling, and experimentation for a dynamic three-sided marketplace.

You will mentor a team of scientists, partner with stakeholders to identify needs, and communicate findings to senior leadership while owning the product development cycle from data and modeling to measurement and impact.

Qualifications

  • PhD/MS/Bachelor in quantitative fields (Economics/Statistics/ML/OR)
  • 7+ years industry experience as Applied/Data Scientist (or 4+ years with PhD)
  • 1+ year managing a team of scientists
  • Excellent communication and collaboration skills across product areas and leadership
  • Background in at least one programming language (Python, R, Scala/Spark)
  • Experience designing experiments and interpreting results across KPIs

Responsibilities

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

Skills

Team leadership
Communication
Programming (Python/R/Scala/Spark)
Experiment design

Education

PhD/MS/Bachelor in Economics/Statistics/ML/OR

Job description

About the Role

End-to-end product development from a data, analytics, modeling, and experimentation perspective. Specifically, formulating ambiguous business problems, prototyping various optimization & causal inference & marketplace dynamics & machine learning models, producing data insights, and designing & analyzing experiments.

About the Team

The Uber Eats Marketplace team is the heart of the Uber Eats business. We build the platform and products that power the magical experience of connecting eaters, couriers, and restaurants. As a critical component of this ecosystem, the Consumer Pricing and Incentives team is responsible for the complex systems that determine the price users pay for every Uber Eats delivery worldwide.

Our mission is to build and refine a fully automated pricing system that optimizes our three-sided marketplace for consumers, couriers, and merchants. We leverage sophisticated optimization, machine learning, and causal inference techniques to balance efficiency, reliability, and cost under highly dynamic conditions. This is a high-impact team solving core business challenges across diverse verticals—including restaurant delivery, grocery, and retail—and supporting global markets with unique and complex problems.

What you will do
  • Lead a team of Scientists, including growing and mentoring your team members.
  • Partner closely with cross-functional stakeholders and other Science teams to identify business needs and translate them into technical roadmaps to deliver impactful solutions.
  • Communicate complex findings and recommendations to senior leadership.
  • Solve ambiguous, challenging 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 how our teams measure success by developing metrics in close partnership with cross-functional partners.
Basic Qualifications
  • Ph.D., M.S. or Bachelor's degree in Economics, Statistics, Machine Learning, Operations Research, or other quantitative fields.
  • 7+ years of industry experience as an Applied or Data Scientist or equivalent (or 4+ years with Ph.D.).
  • 1+ years managing a team of scientists.
  • Excellent communication and collaboration skills: Able to lead initiatives across multiple product areas and communicate findings with leadership and product teams.
  • Background in at least one programming language (e.g., Python, R, Scala/Spark)
  • Experience designing experiments and interpreting the results to draw detailed and actionable conclusions across a variety of key performance indicators
Preferred Qualifications
  • Ph.D. in Economics, Statistics, Machine Learning, Operations Research, or other quantitative fields.
  • 2+ years managing a team of scientists.
  • Experience in leading key technical projects and substantially influencing the scope and output of others.
  • Thought leadership to drive cross-functional projects from concept to production.
  • Experience in large-scale marketplace algorithm design or experimentation platform.

For New York City, NY-based roles: The base salary range for this role is USD $216,000 per year - USD $240,000 per year.


For San Francisco, CA-based roles: The base salary range for this role is USD $216,000 per year - USD $240,000 per year.


For all US locations, 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.

Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence.

Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.

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