Scientist II, Tech - Matching Team

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 the Candidate Will Need / Bonus Points

---- What the Candidate Will 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., M.S. or Bachelor's degree in Statistics, Economics, Mathematics, Computer Science, Machine Learning, Operations Research, or other quantitative fields.
• Minimum 2 years of industry experience as an Applied or Data Scientist or equivalent.
• Proficient in SQL, Python/R to able to work efficiently at scale with large datasets
• Knowledge of experimental design and analysis (A/B, Switchbacks, Synthetic Control, Diff in Diff etc)
• Experience with exploratory data analysis, statistical analysis and testing and model development

---- Preferred Qualifications ----

• Ability to work in self-guided manner
• Good communication skills across technical, non-technical and executive audiences
• Have a growth mindset; love solving ambiguous, ambitious and impactful problems
• Experience in optimization and/or algorithm development
• Experience with dashboard / data visualization tools (i.e Tableau, Mixpanel, Looker or similar)
• Experience working on online experiments

For San Francisco, CA-based roles: The base salary range for this role is USD $161,000 per year - USD $179,000 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.

Ready to Ride?

This isn't the kind of place where you follow a playbook - it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves - we'd love to hear from you.

You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our 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. Ask your Recruiter for details about this role's requirements.

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.