Data Analyst interview
at Airbnb.

Tell-me-about-a-time stories on ownership, conflict, and impact — scored against this company's real values.

1. 01 Tell us how a piece of analysis you delivered advanced Airbnb's mission of helping people belong, and how you measured that impact.
2. 02 Describe a time you were a host to a stakeholder by translating messy data into a clear, caring recommendation they could act on.
3. 03 Tell us about a time you embraced the adventure and dug into an ambiguous business question no one had defined for you.
4. 04 Walk us through a moment when your dashboard or analysis changed a product decision, and how you championed the data against pushback.

The hard screen for the craft itself — talked through out loud, not whiteboarded in your head.

1. 01 Write a SQL query to find the average number of guests per booking in each city using Airbnb's bookings table.
2. 02 Write a SQL query to retrieve listings in a given set of cities that have at least 10 reviews and an average rating of 4.5 or higher.
3. 03 Given a search-to-book funnel, write SQL to compute drop-off at each stage and identify the city with the worst host-activation rate.
4. 04 How would you define and calculate booking conversion rate, nights booked, and the guest-to-host ratio, and which would you watch to detect marketplace imbalance?

Open-ended design of the systems this company actually runs, with the interviewer probing your tradeoffs.

1. 01 Design the metrics framework and dashboard you'd build to monitor the health of Airbnb's search-to-book funnel across markets.
2. 02 Design a reporting pipeline that segments hosts by activation and retention to inform where Airbnb should invest in supply.
3. 03 Design an analytics data model over bookings, listings, and reviews that lets analysts self-serve common marketplace questions.
4. 04 Design the measurement plan and reporting for evaluating whether a new pricing-suggestion feature increased host earnings and bookings.