title: "Data Scientist Interview Questions at Airbnb (2026 Guide)" slug: "airbnb-data-scientist-interview-questions" description: "Airbnb data scientist interview: rounds, SQL, experimentation, take-home and case questions, plus FAQs for 2026."
Data Scientist Interview Questions at Airbnb (2026 Guide)
Airbnb's data scientist interview runs 4-6 rounds: recruiter screen, a technical screen (SQL plus stats), a well-known take-home analysis challenge on many tracks, then an onsite with a take-home presentation, an experimentation/stats round, an SQL or coding round, and cross-functional plus core-values conversations. Difficulty is moderate-to-hard. Airbnb pioneered much of modern growth experimentation, so A/B testing depth and clear storytelling with data are the twin bars. Expect 4-6 weeks.
Airbnb Data Scientist Interview at a Glance
| Stage | Format | Typical Duration | Focus |
|---|---|---|---|
| Recruiter screen | Phone | 30 min | Track: Analytics, Inference, or Algorithms |
| Technical screen | Video | 60 min | SQL + probability/stats |
| Take-home | Async | Several hours over 2-7 days | Real dataset, open-ended analysis |
| Onsite: presentation | Video | 60 min | Defend the take-home to a panel |
| Onsite: experimentation + SQL | Video | 45-60 min each | A/B design, metrics, queries |
| Cross-functional + values | Conversation | 45 min each | Partnering, mission fit |
Estimates from candidate reports; the Algorithms track adds ML modeling and coding depth.
Real-Style Interview Questions by Round
SQL and coding
- Compute booking conversion by search-to-book funnel step, by market, for the last 90 days.
- Find hosts whose occupancy rate is in the top decile of their city (window functions).
- In Python, clean a listings dataset with mixed currencies and missing nights, then justify each choice.
Statistics and experimentation
- A/B test a new cancellation policy. What's the randomization unit — guest, host, or listing? Defend it.
- Your booking-rate experiment is flat overall but +5% in one segment. What do you do?
- Explain power analysis and pick a sample size for a 1% MDE on conversion.
- How do you test changes to search ranking when treatment leaks through the marketplace?
- When would you use difference-in-differences instead of an A/B test at Airbnb?
Product case
- Nights booked dropped 6% in a major market. Diagnose.
- Define the metrics tree for Airbnb Experiences. What's the guardrail set?
- Should Airbnb show total price upfront everywhere? Predict the metric impacts.
Behavioral and values
- Walk me through an analysis that changed a roadmap.
- Tell me about presenting an unwelcome result to leadership.
- What does "belong anywhere" mean for how you analyze guest data responsibly?
FAQs
How hard is the Airbnb data scientist interview? Moderate-to-hard, with the take-home presentation as the make-or-break round. Panels probe every assumption.
How long is the take-home? Officially bounded (commonly a few hours across several days); strong submissions include a clear narrative, not just notebooks (candidate reports).
What tracks exist? Analytics, Inference, and Algorithms — the last is ML-heavy with coding rounds.
What experimentation topics come up most? Randomization units in a two-sided marketplace, interference, power, and guardrail metrics.
Do values interviews apply to data scientists? Yes — the core values rounds are company-wide and taken seriously.
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