Uber Data Scientist Interview Experiences 2026

Real, anonymous reports from people who interviewed for Data Scientist at Uber, newest first and distilled into what to expect across the loop.

Get your personalized Uber Data Scientist prep plan

Answer 3 quick questions and we will build a free study plan with the exact topics and questions to focus on.

Build my free plan

Hot & recentNewest first

1 month ago

Average Positive San Francisco, CA

After a recruiter call, I went straight into a live 45-minute SQL screen. The questions leaned heavily on advanced SQL window functions, and there were also some metric diagnostic prompts where I had to reason about what the numbers were telling me.

A few days later, I went through a 5-round virtual onsite loop: product sense, stats and experimentation, applied modeling, data processing, and a behavioral bar raiser conversation. The stats and experimentation round felt like the real filter. They didn’t let me get away with a generic “try an A/B test” answer. The discussion pushed on network effects and driver cannibalization, and I had to talk through switchback experimentation and synthetic control ideas with confidence. The product sense part was root-cause analysis, including working through an example where rider cancellations jumped in a specific city and walking through exactly which metrics I’d pull and how I’d interpret them. In modeling, the focus was less on doing math for its own sake and more on handling imbalanced data and choosing tradeoffs for production.

2 months ago

Average Negative San Jose, CA

My interview started with a stats coding round where I coded for an expected value style problem. After that, the second round was a case study, and it ended up being quite easy relative to the coding portion.

The contrast between the two rounds stood out immediately: the first round required careful implementation thinking, while the case study felt more about straightforward reasoning. I kept my focus on explaining my approach, but the overall difficulty level still felt average rather than brutal.

Unlock every Data Scientist interview experience

Real Data Scientist interview experiences

Difficulty, sentiment and outcomes
New reports added every week

See all experiences

Share your interview experience

Interviewed here recently? Add yours to help the next candidate. You'll appear as Anonymous.

What to expect

Distilled from the reports

Recruiter & Initial Screening

The interview process typically begins with a recruiter call that covers the candidate's background and the role's expectations, followed by a technical screening that often includes SQL and sometimes Python. Candidates noted that the recruiter process was generally organized and informative, setting a professional tone for subsequent interviews.

Recruiter callRole expectationsInitial screening

Technical / Coding Screen

Candidates experienced a technical screen that heavily emphasized SQL, particularly advanced concepts like window functions, along with some Python coding. The technical round was often seen as a critical filter, where performance here significantly influenced overall assessment.

SQLPythonTechnical screening

Onsite Loop Structure

The onsite interview loop typically consists of multiple rounds focusing on diverse areas such as product sense, statistics, experimentation, and behavioral assessments. Candidates reported that the interviews were designed to evaluate both technical skills and the ability to reason through complex product-related scenarios.

Onsite loopProduct senseBehavioral assessment

Focus on Experimentation & Metrics

A significant emphasis was placed on experimentation design and metrics interpretation, with candidates expected to discuss A/B testing and product metrics in depth. Interviewers sought nuanced understanding rather than generic responses, making this a key area of evaluation.

A/B testingExperimentationMetrics interpretation

Behavioral & Values Assessment

Behavioral interviews often involved discussions about past projects and how candidates drove business impact, focusing on their ability to challenge assumptions and communicate effectively. This aspect was crucial for determining cultural fit and alignment with Uber's values.

Behavioral interviewCultural fitPast projects

Overall Difficulty & Candidate Experience

Candidates found the overall interview process to be challenging but engaging, with a strong focus on clarity of thought and communication. Many noted that the interconnected nature of questions across rounds made it essential to maintain context and articulate reasoning effectively.

DifficultyCandidate experienceCommunication