2026 Data Science Intern, US

Job Description

About the Role

We're looking for current students to join Uber as data scientist interns during summer 2026 (12 weeks). You will be embedded in a team and work closely with data scientists, engineers, and product managers under the supervision of an analyst on that team.

About the Teams

The Identity Science team develops identity verification-based solutions to prevent fraud and safety incidents from happening. Not only is that the right thing to do but making Uber a safer platform has potential to foster long term growth. We do that by focusing both at the forest (e.g. with machine learning models) as well as the trees (e.g. with deep dive investigations of individual cases).

The Safety Science team specializes in rare events and available safety tools. 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 Risk team provides insights and develops machine learning models and strategies to combat payment fraud, protects our customers and business against financial loss, and minimizes credit risk for financial products. Working in the risk domain is somewhat similar to playing an adversarial game with fraudsters: you will frequently work to identify new fraud patterns (often at a granular level) and provide scientific solutions to address emerging risk problems (at scale/globally). Our goal is to deliver innovative risk management across Uber's marketplaces to maximize legitimate revenue and sustainable growth, while minimizing fraudulent transactions.

The Customer Obsession Data Science team is responsible for ensuring every Uber customer support experience is extraordinary. Specifically, this team works to build self-service technology, including leveraging GenAI, that are deeply coordinated with the Uber customer support experience, making it easy for our customers and customer support representatives to get to the right outcome faster. We are also responsible for optimizing support policies, identifying customer intentions, proposing the best solutions with personalization, and help improve the overall customer experience with Uber.

What You'll Do

• Collaborate with your designated mentor to define the problem, scope your project, develop and prototype the solution, and measure the impact
• Conduct deep data analysis to drive business decisions
• Develop and validate critical data pipelines
• Develop and monitor product metrics via dashboards to measure product performance
• Partner with engineers, data scientists, and product managers to understand business use cases
• Design and develop solutions, and present findings
• Connect with partners, cross-functional teams, and senior management

• Current Bachelor's or Master's students pursuing a degree in Data Analytics, Data Science, Mathematics, Statistics, Computer Science, Economics, Engineering, Math, Physics or other related analytical fields
• Candidates must have at least one semester/quarter of their education left following the internship
• Coding proficiency in SQL
• First principle thinking, problem-solving, and critical thinking skills

• Proficiency in AB Testing
• Proficiency in Python
• Prior work experience in an analytical setting
• Organized, detail oriented, and able to work independently on multiple projects at once
• Ability to communicate effectively with both technical and business partners
• Proficiency with office efficiency tools including email, web browser, web apps, database search, spreadsheets/word processors (Google Apps)
• Self starter, taking initiative keeping relevant partners in the loop
• Open to feedback, excellent at implementing newly learned ideas and concepts
• Background in data visualization via open-source libraries/packages or third-party tools (i.e. Tableau, Mixpanel, Looker, or similar)