About The Role

Mobility Data Science at Uber uses data to improve and automate all aspects of Uber's core ridesharing products. You will be joining the Driver Structural Pricing team, which owns our automated Driver Incentives algorithms and platform. You will work on designing and targeting incentive structures that make driving, and driving specifically with Uber, highly attractive from a driver perspective while also improving the efficiency of the Uber marketplace. Some examples of the exciting projects you may contribute to include optimizing promotions to encourage drivers to drive in times and places of peak rider demand, building incentive-compatible menus for drivers who reach a certain number of trips each week, and creating driver subscription passes.

We are looking for candidates with a passion for solving new and difficult problems with data. In the role, you will be able to use your strong quantitative skills in the fields of economics, machine learning, statistics, computer science, and/or operations research to improve outcomes for Uber's drivers and overall marketplace.

What The Candidate Will Need / Bonus Points

---- What the Candidate Will Do ----

• Build statistical, optimization, and machine learning models for applications including pricing, targeting, and experimentation.
• Work with engineers and product managers to turn data science prototypes into robust, reliable solutions.
• Present findings to business leaders to inform decisions.
• Solve ambiguous, challenging business problems using data-driven approaches.
• Work closely with multi-functional leads to develop technical vision and drive team direction.
• Establish standard methodologies for data science including modeling, coding, analytics, optimization, and experimentation.
• Communicate with senior management and multi-functional teams.
  
  

---- Basic Qualifications ----

• Ph.D. or MS degree in, Statistics, Economics, Machine Learning, Operations Research, Computer Science or other quantitative field. (If M.S. degree, a minimum of 1+ years of industry experience required and if Bachelor's degree, a minimum of 2+ years of industry experience required)
• Knowledge of underlying mathematical foundations of statistics, machine learning, optimization, economics, and analytics
• Knowledge of experimental design and analysis
• Experience with exploratory data analysis, statistical analysis and testing, and model development
• Ability to use a language like Python or R to work efficiently at scale with large data sets
• Ability to use languages and tools like SQL, Hive, and Spark
  
  

---- Preferred Qualifications ----

• Industry experience working as an Applied Scientist or similar
• Experience in experimental design and analysis (e.g., A/B and market-level experiments), as well as causal inference
• Experience in algorithm development and prototyping
• Experience with causal ML methods is a plus
• Technical leadership experience and passion for mentoring
• Experience productionizing algorithms for real-time systems
  
  

Uber is proud to be an Equal Opportunity/Affirmative Action 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 .

Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.