Description
Uber is hiring an Applied Scientist for its Rider Pricing and Incentives Science team to build, scale, and optimize statistical, mathematical programming, and machine learning models for dynamic pricing. The role involves generating data insights, developing experimentation and causal inference methods, collaborating with Product, Engineering, and Operations, translating marketplace data into business strategies, and building diagnostic tools and metrics. Candidates need a quantitative degree, 5+ years of relevant industry experience or 3+ years with a Ph.D., expertise in optimization, statistics, machine learning, or econometrics, and proficiency in Python/R and SQL. The role is available in New York City, San Francisco, Seattle, Sunnyvale, and other United States locations, with a base salary of USD $190,000 to USD $211,000 per year.
