Uber-posted 23 days ago
Intern
San Francisco, CA
5,001-10,000 employees
Transit and Ground Passenger Transportation

We're looking for Ph.D. students specializing in Applied Science to intern during Summer 2026 (12 weeks). As a Ph.D. intern, you will be embedded in a product team working on solving real-world Uber problems and will have the opportunity to partner closely with other Applied and Data Scientists, Software Engineers, Product Managers, and other cross functional partners. About the Team The Road Safety team applies data science and analytics to safety initiatives that make rare safety events even rarer. As a member of the team you will conduct deep-dive analyses, design and analyze experiments, and support the development of machine learning models to make our platform as safe as possible for all users. You will play an influential role in driving critical product and policy decisions.

  • Work with a mentor closely to define a business problem, scope a project, develop, and prototype the solution using data-driven approaches
  • Perform deep-dive analyses to discover root causes for safety issues and changes in trends
  • Present findings to leaders to inform decisions
  • Support statistical and machine learning efforts including modeling, experimentation, signal processing, time series analysis, geospatial analysis, natural language processing, and more
  • Current Ph.D. student majoring in Operations Research, Mathematics, Computer Science, Statistics, Machine Learning, or other related quantitative fields. Candidates should have at least one semester/quarter left of their education after finishing the internship.
  • Knowledge of underlying mathematical foundations of statistics, machine learning, optimization, economics, and analytics
  • Knowledge of experimental design and analysis
  • Knowledge of causal inference
  • Strong problem solving and analytical abilities
  • Familiarity with SQL
  • Familiarity with a programming language such as R and Python
  • Ability to communicate effectively with both technical and business partners
  • Research mentality with a bias towards action to structure a project from idea to experimentation to prototype to implementation
  • Independence, excellent communication, and outstanding follow-through - you energetically tackle your work and love the responsibility of being individually empowered
  • Experience with exploratory data analysis, statistical analysis, model development, and causal inference.
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