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2024 PhD Applied Scientist (Non-Econ) Intern, United States

Logo of Uber


21d ago

🚀 Off-cycle Internship

San Francisco

AI generated summary

  • You must be a current Ph.D. student in machine learning, computer science, or related fields with strong mathematical foundations and analytical skills. Familiarity with SQL, Python, and data pipelines for ML models is a plus. Good communication and research mentality are preferred.
  • You will work on marketing projects, prototype models using data-driven approaches, collaborate with engineers and product managers, present findings to leaders, establish standard methodologies for science, and conduct experiments to drive business decisions.

Off-cycle Internship

DataSan Francisco


  • The Marketing Personalization and Targeting team is looking for PhD student interns for Summer 2024. Our internships are 12 weeks long. As an 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. It is a challenging but fun environment!


  • Current Ph.D. student majoring in Machine Learning, Computer Science, Statistics, Operations Research and Mathematics, or other related quantitative fields. Candidates should have at least two semesters/quarters left of their education after finishing the internship.
  • Knowledge of underlying mathematical foundations of optimization, statistics and machine learning
  • Strong problem-solving and analytical abilities
  • Familiarity with SQL
  • Familiarity with Python
  • Preferred Qualifications:
  • 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 take on your work and love the responsibility of being individually empowered
  • Experience with exploratory data analysis, statistical analysis and model development
  • Experience with building data pipelines for machine learning models.
  • Familiarity with a Spark and/or Pyspark

Education requirements

Currently Studying

Area of Responsibilities



  • Marketing applied science informs decisions across Uber's global marketing efforts, accelerating both demand and supply growth worldwide. We use advanced statistical modeling, machine learning, or data mining techniques in a scalable manner including large scale data processing such as Spark, Hive, and Uber's proprietary machine learning platform, and more. Interns on the team will work on projects such as:
  • Assisting in prototyping causal inference methods and econometric models to inform the efficiency of our marketing spend
  • Building machine learning and reinforcement learning models to aid in the growth and profitability of different Uber products (Uber Rides Pass, Eats Pass, etc.)
  • Architecting a recommendation system to understand cuisine preferences at a user-level
  • Standardizing marketing models and enhancing their scalability and stability through platformization
  • Identifying and implementing improvements to our bid, budget and creative optimization algorithms on Uber’s advertising channels like Google, Facebook, etc.
  • What You’ll Do:
  • Work with a mentor closely to define a business problem, scope a project, develop, and prototype the solution using data-driven approaches
  • Work with engineers and product managers to turn prototypes into scalable solutions
  • Present findings to leaders to inform decisions
  • Establish standard methodologies for science such as modeling, coding, analytics, optimization, and experimentation
  • Conduct experiments to drive business decisions


Work type

Full time

Work mode



San Francisco