The Driver Pricing science team at Uber is looking to solve the problem of optimizing driver offer pricing algorithms, driver promotions, and driver positioning to drive marketplace efficiency, consistency, and long term driver health.
Requirements
- Experience with experimental design, exploratory data analysis, statistical analysis, causal inference, and model development
- Proficient in both a data ETL language (e.g. SQL) and a scripting language like Python or R for data analysis
- Experience in building and managing high performance science teams - including mentoring and coaching senior ICs and people managers
- Track record in prioritizing and driving multiple work-streams forward simultaneously
- Ability to empower a team while providing them with career paths that align with business goals
- Proven track record of collaborating with and influencing stakeholders
Responsibilities
- Manage and support a team or scientists and science managers
- Work with eng and product partners to continuously optimize key pricing and promotion systems
- Come up with metrics and measurements/ experimentation methodology to learn about the impact of these systems
- Work with business/operations teams to give insights about marketplace health, earnings health, and help solve global business problems.
Other
- Ph.D. degree in Math, Economics, Bioinformatics, Statistics, Engineering, or other quantitative fields
- Minimum of 7 years of experience with 4 years of people management experience
- Excellent storyteller with the ability to translate deep technical subjects into understandable narratives for non-technical audiences
- Able to build a clear technical vision of the system that balances customer empathy, business needs and practical considerations
- 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
