Airbnb Business Analyst candidates describe a recruiter screen, a hiring manager conversation and, in some reports, a timed case study. Expect project deep-dives, business judgment and product-use questions.
$135K
Avg. Base Comp
$190K
Avg. Total Comp
Not reported
Typical Rounds
Not reported
Process Length
Candidates who describe the Airbnb Business Analyst process report that it leans more toward business judgment and project ownership than toward pure technical drills. Two candidates describe an early recruiter or HR conversation followed by a hiring manager round. One of them says the manager round felt like a test of whether they understood the business side of the role.
The most concrete reported question was how to determine and evaluate underperforming listings. The same candidate was asked about a hard decision they had made and says interviewers seemed to care whether they actually use Airbnb. Another candidate was asked to walk through owned projects, ambiguous business problems, stakeholder work and data-driven recommendations. Follow-ups pushed on why they chose an approach, how they validated the data and what they would do differently. That candidate also describes a 90-minute case study with 60 minutes to analyze material using any tools, up to 15 minutes to present and about 15 minutes of Q&A.
A third candidate reports a longer process of more than a month. It included stakeholder interviews, a values conversation and a director-level round. Questions included proposing improvements to the Airbnb website and discussing biggest mistakes. That candidate also reports a verbal offer that was later rescinded, so confirm each step with your recruiter.
In practice, prepare two or three project stories you can defend in detail. Practice a structured read on listing quality and marketplace health, and form an honest view of the product as a user. Outcomes in these reports were mixed: one no offer, one rescinded offer and one still waiting. Only a few candidates reported, so treat the process as variable.
Synthesized from 4 candidate reports by our editorial team.
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Real interview reports from people who went through the Airbnb process.
The process started with an initial conversation where the focus was less on rehearsed answers and more on how I actually think and work. I was asked about projects I had owned, how I approached ambiguous problems, worked with stakeholders, used data to make decisions, and handled situations when things did not go according to plan.
The parts I felt most confident in were the project and behavioral questions because I could pull from real examples and explain my thought process, not just the outcome. The moments that made me think harder were the follow-up questions. They would take one answer and go a level deeper: Why did you choose that approach? What would you have done differently? How did you know your recommendation was working?
What surprised me most was how conversational the interview felt. It did not feel like a checklist of questions. It felt more like the interviewers were trying to understand how I would operate on their team. By the end, I realized that being able to structure an unclear problem, defend my reasoning, and communicate simply mattered just as much as having the technical answer.
Questions asked: From what I remember, the first round was a mix of behavioral, analytical, and project-based questions. They spent a lot of time digging into projects I had actually worked on rather than asking textbook questions. I was asked to walk through examples of how I approached an ambiguous business problem, how I used data to identify what was happening, how I worked with stakeholders, and how I turned the analysis into a recommendation.
There were also follow-ups around the tools and methods I mentioned. For example, if I talked about SQL, dashboards, automation, or reporting, they wanted to understand what I personally built, how I validated the data, what metrics I selected, and how the final output influenced a business decision. A lot of the questions were basically, “Why did you choose that approach?” and “What would you do if the data told you something different from what the stakeholder expected?”
The next round was a 90-minute case study with the same managers. The instructions were unusually open-ended. I would receive the case material either the day before or the day of the interview, then have 60 minutes to analyze it using any tools I wanted. After that, I would have up to 15 minutes to present my findings and recommendations, followed by roughly 15 minutes of Q&A.
What stood out was that they were not just testing whether I could calculate the right number. The case was designed to see how I structured an unfamiliar problem, checked the data, decided which metrics actually mattered, identified the business story, made assumptions when information was missing, and translated everything into a recommendation that leadership could act on. I also expected the Q&A to challenge assumptions, outliers, comparability, business impact, and why I recommended one action over another.
There was no long take-home assignment or requirement to use a specific software. The freedom to use any tool actually made it more challenging because you had to decide very quickly what analysis was worth doing and what was just noise.
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Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
Featured question at Airbnb
Write a query that returns all neighborhoods that have 0 users.
| Question | |
|---|---|
| Hurdles In Data Projects | |
| Success Measurement | |
| Order Addresses | |
| Trial User Segmentation | |
| Uber User Journey | |
| Causal Email Journey | |
| Data Pipelines and Aggregation | |
| Model Product Performance Degradation | |
| String Palindromes | |
| Approval Drop | |
| Listing Bookings Aggregation | |
| Deciding Between Solutions | |
| Client Solution Pushback | |
| Payment Data Pipeline | |
| Underpricing Algorithm | |
| Docs Metrics | |
| Reward Experiment | |
| Statistically Significant Test | |
| Google Docs Drop | |
| Interpreting Fraud Detection Trends | |
| 2nd Highest Salary | |
| Button AB Test | |
| 500 Cards | |
| Experiment Validity | |
| Bagging vs Boosting | |
| Month Over Month | |
| Rolling Bank Transactions | |
| WAU vs Open Rates | |
| Employee Salaries |
Synthesized from candidate reports. Individual experiences may vary.
Candidates report an initial recruiter or HR conversation covering their background and why they fit the role. One candidate says compensation was walked through up front. Timing may vary, and one candidate reports that recruiter outreach came about two months after applying.
Candidates report a hiring manager round that tests how you think. Reported questions include a hard decision you made, how to evaluate underperforming listings, and walking through owned projects and ambiguous problems. Candidates describe follow-ups on why you chose an approach, how you validated data and what you would change.
One candidate describes a 90-minute case study with the same managers. Case material arrived the day before or the day of, followed by 60 minutes of analysis with any tools, up to 15 minutes of presentation and about 15 minutes of Q&A. Expect to structure an open-ended problem and defend your recommendation, though not every candidate reports this round.
One candidate reports further rounds with another team lead, a values interviewer from a different department and a director. Topics included proposing website improvements, biggest mistakes and lessons, and how they would approach the company differently. Another candidate expected team interviews next. The number of later rounds may differ by team.
