PhD Scientist Intern; Earner

Position: 2026 PhD Scientist Intern (Earner Growth), US
We're looking for PhD candidates to work with the Earner Growth team as a Scientist intern during summer 2026 (12 weeks). As an intern, you will be embedded in a product team working on solving real-world Uber problems under the supervision of an analyst on that team, and will have the opportunity to partner closely with Scientists, Software Engineers, Product Managers, and other cross functional partners.

About the Role

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 Uber Eats 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 is for you. In our Sciences division, we strive to make magic within Uber's marketplace. This requires judgment to make difficult trade-offs, blending algorithms with human resourcefulness, and the ability to build simplicity from complexity. When we get the balance right for everyone, Uber magic happens. We build systems to peer into the future to craft the most cost-efficient marketplace for matching supply and demand.

We are passionate about using innovative 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 and use data to inform product decisions, build models to power our solutions, and also develop platform tools that are used across teams with a primary focus on Mobility and Delivery. We work with millions of earners across the globe to make this magic happen and want you to join us!

About the Team

Earners (drivers and couriers) are an integral part of Uber's multi-sided marketplace. They provide the time and the means to move people and things. Importantly, they enable the connection between the physical and digital world to make the movement happen at the push of a button for everyone, everywhere.

Within Uber, Earner Growth plays a critical role in earners' journey as the team is responsible for earner onboarding, activation, early life cycle, and resurrection. This presents the teams with the opportunity to shape and tailor the product experience during earners' many firsts (i.e., first time interacting on the Uber platform, choosing the earning opportunity, going online, receiving incentive offers, completing a trip, or reading the earnings summary).

These firsts can be daunting.

Therefore, making sure that the earner journey is great at every touch point is important to build trust with Earners, communicate Uber's value proposition, and ensure each firsts to be a great experience.

Growth interns will tackle problems such as:

* Developing innovative new earner incentives that earners for choosing our network and optimizing Uber's new earner incentives spend

* Optimizing Uber's background check spend and onboarding funnel

* Designing recommendation engines to recommend the most relevant earning opportunities and early lifecycle content

* Developing matching algorithms for driver to driver mentorship program

* Modeling and predicting earner behaviors to improve earner experience throughout the onboarding funnel

* The team employs a variety of ML/AI techniques, spanning from causal ML meta learners, supervised ML, RL multi-armed bandits, genAI LLM to deep learning embeddings to build impactful data products.

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

* Pursuing a Ph.D. majoring in Computer Science, Machine Learning, Economics, Operations Research, Statistics, or other related quantitative fields

* Candidates should have at least one semester/quarter left of their education after finishing the internship

* Strong problem solving and analytical abilities

Preferred Qualifications

* Coding proficiency in areas such as Python, Java, Go, Spark, and SQL

* Knowledge of underlying mathematical foundations of statistics, machine learning, optimization, stochastic processes, economics, and analytics

* Experience in the following areas:
Exploratory Data Analysis, Statistical Analysis, Model Development, Operations Management, Revenue Management and Pricing, Advertising, Experimental Design, Assortment Planning, Transportation

* Background in data visualization via open-source libraries/packages or third-party tools (i.e. Tableau, Mixpanel, Looker, or similar)

* 0-2 years of prior work experience in an analytical setting

*…