2023 PhD Applied Scientist Internship
The Uber Core Analytics & Science, Core Services, and Platform Engineering Data Science teams are looking for graduate student interns for Summer 2023. Our internship program is 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.
About the Roles
Have you ever ordered a car service on Uber, and when the ride arrives, wondered how it got to you so fast? Ever ordered food on UberEats and wondered where the driver was before receiving your order and how long it took to get to the restaurant or if your order was ready when the courier arrived? Ever wondered why your grocery delivery from Uber always has the best apple picked? If so, Uber Core Analytics & Science (CAS) is for you. In CAS, we strive to make magic within Uber’s marketplace. This requires judgment to make difficult trade-offs, blending algorithms with human ingenuity, and the ability to create simplicity from complexity. When we get the balance right for everyone, Uber magic happens. We build systems to peer into the future to design the most cost-efficient marketplace for matching supply and demand. CAS is focused on using cutting edge economics, machine learning, and scalable distributed software that automates and optimizes every aspect of this intricate dance between participants of the marketplace.
We are involved in every stage of the product development cycle. We use data to inform product decisions, build models to power our solutions, and also develop platform tools that are used across teams. We focus primarily on Mobility and Delivery. In 2021, we drove tens of billions of dollars in Gross Bookings. Just in the fourth quarter of 2021, we booked nearly 2 Billion trips worldwide at a growth rate of 23% year over year. We work with millions of earners across the globe to make this magic happen and want you to join us!
- Delivery: UberEats is Uber's on-demand food, grocery and convenience delivery business. It currently operates in over 45 countries. Delivery is a 3-sided marketplace, consisting of Eaters, Couriers, and Merchants. Projects include optimizing our eater pricing systems, designing the best menu of delivery and service fees for members and non-members, improving matching algorithms to get the food to you at the right time (and right temperature!), building an ads delivery system, modeling and predicting eater and courier behavior, and improving the efficiency of user acquisition, promotions, courier experience, and merchant onboarding, among many others.
- Mobility: Rides Applied Science at Uber uses data to improve and automate Uber's core ridesharing products. Rides interns will tackle problems such as optimizing Uber’s short and long term pricing systems; efficiently matching incoming trip requests in Uber’s dispatch system; developing innovative incentives that reward riders and drivers for choosing our network; developing algorithms and experimentation to make our rider and driver experience stand out. We also forecast, monitor, and evaluate all aspects of our marketplace and user behavior using both large scale observational data and meticulous experimentation.
Core Services is hiring interns for two teams: Risk and Safety & Insurance.
Our Risk Applied Science team provides insights and develops machine learning models and strategies to combat payment fraud and marketplace abuse, improve account security and integrity, and minimize credit risk for financial products. Working in the risk domain is like playing an adversarial game with fraudsters: you will frequently work to identify new fraud patterns and provide scientific solutions to address emerging risk problems at scale.
The Safety and Insurance Applied Science team specializes in rare events. The team works closely with partners to build new product features, implement machine learning algorithms, and optimize safety policies to help reduce safety incidents and make it safer for riders, drivers, eaters, restaurants, and all people who use Uber's platform. This team pursues some of the hardest problems in all of Uber: improving the safety of cities and people all over the world. This position focuses on algorithmic solutions to understanding and improving interpersonal safety.
The Platform Engineering Data Science (PEDS) is hiring interns for their team. As a centralized data science function, the team will be built in the Platform Engineering organization but will derive its backlog from problems across platform engineering. The PEDS team is a central data science function for Platform Engineering; its scope includes problems across the entire organization. Key problems in its purview may include automated, meaningful assessment of company-wide reliability and outage impact, analysis of contributors and impediments to engineering productivity, risk scoring to assist in code review, predictive models for capacity planning and service scaling, automatic tuning of parameters like deployment speed, and Root-cause recommender systems to aid in outage debugging and automated rollback.
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
Basic Qualifications
- 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 optimization, stochastic processes, statistics and machine learning
- Strong problem solving and analytical abilities
- Familiarity with SQL
- Familiarity with a programming language such as R and 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 tackle your work and love the responsibility of being individually empowered
- Experience with exploratory data analysis, statistical analysis and model development
- Experience in the following areas: Operations Management, Revenue Management and Pricing, Advertising, Experimental Design, Assortment Planning, Transportation