Uber is looking to improve the efficiency and reliability of its marketplace by analyzing data to design and automate 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
- Scientists at Uber use data to analyze, improve and automate all aspects of Uber's core rideshare and delivery products.
- You will be joining the Rider Pricing and Incentives team, which owns our automated real-time pricing and incentives algorithms and platform.
- You will work on analyzing data that help design the models that maintain reliability and improve the efficiency of Uber's Mobility marketplace.
- We are looking for experienced candidates with a passion for analyzing data and solving new and difficult problems with data.
- Well-honed communication and presentation skills.
