Senior Applied Science Manager - Marketplace
Sunnyvale, CA, USA
Posted on Wednesday, August 2, 2023
About The RoleApplied Scientists at Uber use data to improve and automate all aspects of Uber''s core rideshare and delivery products. You will be joining the Consumer Incentive team. The team heavily invests in machine learning, causal inference, constrained optimization, distributed system, etc to optimize/personalize incentive structures to increase consumer engagement. The team is critical in fostering a healthy ecosystem and in providing a pleasant and sticky experience for Uber’s customers.We are looking for experienced candidates with a passion for solving new and difficult problems with data. In this role, you will be able to use your strong quantitative skills in the fields of machine learning, and/or operations research to improve the Uber user experience as well as the overall marketplace performance.What You''ll Do
- Build statistical, optimization, and machine learning models for a range of applications in the incentive algorithms space.
- Design and execute product experiments and interpret the results to draw detailed and actionable conclusions.
- Use data to understand product performance and to identify improvement opportunities.
- Present findings to senior management to inform business decisions.
- Collaborate with cross-functional teams across disciplines such as product, engineering, operations, and marketing to drive system development end-to-end from ideation to productionization.
- Ph.D., M.S., or Bachelors degree in Statistics, Economics, Machine Learning, Operations Research, or other quantitative fields.
- Minimum 6 years of industry experience as an Applied or Data Scientist or equivalent.
- Minimum 3 years of management or tech lead experience.
- Knowledge of underlying mathematical foundations of statistics, machine learning, optimization, economics, and analytics.
- Experience in experimental design and analysis.
- Experience with exploratory data analysis, statistical analysis and testing, casual analysis and ML model development.
- Ability to use Python to work efficiently at scale with large data sets.
- Proficiency in SQL.
- 10+ years of industry experience.
- 7+ years in leading Science teams.
- Experience in algorithm development and prototyping.
- Experience in causal ML.
- Well-honed communication and presentation skills.