title: "Data Scientist Interview Questions at Uber (2026 Guide)" slug: "uber-data-scientist-interview-questions" description: "Uber data scientist interview: rounds, SQL, stats, A/B testing and case questions, plus FAQs and prep strategy for 2026."
Data Scientist Interview Questions at Uber (2026 Guide)
Uber's data scientist interview runs 4-5 rounds: recruiter screen, a technical screen mixing SQL and statistics, sometimes a take-home or timed assessment, then an onsite loop with an analytics case study, an experimentation/stats deep dive, a coding round (SQL + Python), and a behavioral round. Difficulty is moderate-to-hard. Uber's signature is product-case questions built on marketplace dynamics: pricing, matching, incentives. Expect 3-5 weeks.
Uber Data Scientist Interview at a Glance
| Stage | Format | Typical Duration | Focus |
|---|---|---|---|
| Recruiter screen | Phone | 30 min | Track (product vs ML), background |
| Technical screen | Video | 45-60 min | SQL, probability, one mini-case |
| Assessment (some tracks) | Take-home/timed | 1-3 hrs | Analysis + writeup |
| Onsite: case + experimentation | Video | 60 min each | Metrics, A/B testing, causal inference |
| Onsite: coding + behavioral | Video | 45-60 min each | SQL/Python, values fit |
Estimates from candidate reports; Uber's "Product Data Scientist" and "Applied Scientist" tracks weight rounds differently.
Real-Style Interview Questions by Round
SQL and coding
- Write SQL to find drivers whose weekly trip count dropped 30%+ two weeks in a row.
- Compute a 7-day rolling average of completed trips per city using window functions.
- In Python, deduplicate overlapping GPS ping intervals per driver.
Statistics and probability
- Riders arrive as a Poisson process at 4/minute. What's the probability of zero arrivals in 30 seconds?
- Explain p-values to a general manager who wants to ship anyway.
- When would you use a bootstrap instead of a t-test?
Experimentation
- Design an A/B test for a new driver incentive. What's your randomization unit and why is city-level interference a problem?
- Your experiment shows +2% trips but -1% driver retention. Ship or not?
- How would you use switchback experiments for surge pricing changes?
Product case
- Airport pickup wait times jumped 20% in one city. Diagnose it.
- Define success metrics for UberPool (shared rides). What guardrails do you set?
- Should Uber raise base fares 5% in a mature market? Structure the analysis.
Behavioral
- Tell me about an analysis that changed a launch decision.
- Describe a time stakeholders misused your numbers. What did you do?
FAQs
How hard is the Uber data scientist interview? Moderate-to-hard. SQL is expected to be fast and fluent; the differentiator is experimentation design under marketplace interference.
What's unique about Uber's experimentation questions? Two-sided marketplace effects. Standard user-level A/B tests break when drivers are shared across arms — know switchbacks and cluster randomization.
Do I need machine learning? Product DS roles: light ML. Applied Scientist roles: full ML depth including modeling rounds.
What language is the coding round in? SQL always; Python (pandas) commonly.
How long is the process? Typically 3-5 weeks (estimate).
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