Uber is looking to improve the efficiency and reliability of its marketplace by analyzing data to design and implement automated real-time pricing and incentives algorithms.
Requirements
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, and model development.
Ability to use Python to work efficiently at scale with large data sets.
Proficiency in SQL.
Experience in algorithm development and prototyping.
Experience with productionizing algorithms for real-time systems.
Responsibilities
Use data to understand product performance and to identify improvement opportunities.
Build statistical, optimization, and machine learning models for a range of applications in the pricing and incentives algorithms space.
Design and execute product experiments and interpret the results to draw detailed and actionable conclusions.
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
Other
Ph.D., M.S., or Bachelors degree in Statistics, Economics, Machine Learning, Operations Research, or other quantitative fields.
2+ years of experience as an Applied or Data Scientist or equivalent (can be also as part of Ph.D training).
2+ years of industry experience.
Well-honed communication and presentation skills.
Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office.
