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Airbnb interview notes, page 7 of 19

Large Enterprises

Most of these Airbnb write-ups come from Software Engineers (141), then Machine Learning Engineers (19) and Data Scientists (12). The most reported rounds are the technical phone screen (85), the system design round (47), the behavioral / leadership round (20) and the product sense round (13).

187 interview notes · updated Oct 2026

Airbnb·Software Engineer·Technical Phone Screen

May 2026
Airbnb software engineer interview with a coding round focused on game board design. The problem had a competitive twist that pushed beyond the usual tic-tac-toe variant most people prep for.
  • Design a data structure for a Connect-N game where pieces fall to the lowest empty cell in a column. Implement a move(column, player) function that returns true if the player has achieved N consecutive pieces in any direction after that move. What's your per-move time complexity and how does your algorithm work?

“My first instinct was to just scan the whole board after every move, which is obviously wrong for a senior-level question.”

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Airbnb·Software Engineer·Technical Phone Screen

May 2026
Airbnb software engineering interview with a pretty gnarly algorithmic problem centered on palindrome pair detection at scale. The question had a lot of moving parts and felt like it was testing whether you'd actually thought about trie-based string processing before.
  • Given an array of distinct lowercase strings, find all index pairs (i, j) where i != j and the concatenation of words[i] + words[j] forms a palindrome. The array can have up to 100,000 words with total character count up to 200,000. You need to beat the naive O(n^2 * L) approach. Walk through your data structure choices, how you handle edge cases like empty strings and single characters, how you prevent duplicate pairs, and give a complexity analysis with test cases.

“This wrecked me a little.”

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Airbnb·Software Engineer·Technical Phone Screen

May 2026
Airbnb software engineer interview that was basically a project deep dive. The interviewer seemed checked out the whole time, which made the whole thing feel kind of pointless.
  • Walk me through a recent project you worked on.

“The vibe was off from the start.”

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Airbnb·Software Engineer·Technical Phone Screen

May 2026
Airbnb coding round, one algorithmic question the whole time. Pretty focused session, nothing too surprising if you've done greedy problems before.
  • Given a string representing a non-negative integer and an integer k, remove exactly k digits so the resulting number is as small as possible. The digit order must be preserved and there should be no leading zeros in the output.

“The monotonic stack solution clicked for me pretty fast, but I fumbled the edge cases.”

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Airbnb·Software Engineer·Onsite - Coding / Algorithms

May 2026
Three coding rounds at Airbnb, two went fine, then the third one had a bug that broke the output on a hard problem. Still not sure if that's an automatic disqualification or not.
  • A hard-level coding problem given in the third round, where a bug in the implementation caused the output to be incomplete.

“The first two rounds felt solid so I went into the third with some confidence.”

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Airbnb·Data Scientist·Take-home Assignment

May 2026
Airbnb DS interview that was basically one big SQL/Python case study disguised as a take-home. The problem looked manageable at first glance until I actually read the attribution rules and edge cases, then it became a whole thing.
  • Given a visits table and a bookings table, deduplicate visits within a 60-second window per user (keep only the latest), then attribute each confirmed booking to the most recent visit by the same user within the prior 24 hours. Compute control vs treatment metrics by day and variant for a 7-day window, including visits, unique users, attributed bookings, conversion rate, total revenue, revenue per visit, cancellation counts, and unattributed confirmed booking counts. Provide SQL or Python and explain your assumptions.
  • Produce a daily line plot of conversion rate for control and treatment with 95% Wilson confidence intervals.
  • How do you handle edge cases like a user appearing in both control and treatment within the same 7-day window, multiple bookings following a single visit, or a booking that falls just outside the 24-hour attribution window?

“The deduplication step is where I stumbled first.”

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Airbnb·Software Engineer·Technical Phone Screen

May 2026
Airbnb SWE interview with a classic graph/BFS problem. Not much context given about how it went but the problem itself is a well-known one if you've done any serious algo prep.
  • Given two strings and a dictionary of valid words, find the minimum number of operations needed to transform the first string into the second, where each intermediate step must be a valid dictionary word.

“Word ladder.”

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Airbnb·Software Engineer·Onsite - Behavioral / Leadership

May 2026
Behavioral round at Airbnb for a software engineering role. One question, structured around a past project with a focus on root cause analysis and cross-team coordination. Pretty standard but the depth they expected was a bit more than I anticipated.
  • Walk me through a significant project you worked on: what caused the major issues, how did you coordinate with teammates to fix them, and what steps did you take to prevent things from getting worse?

“I structured my answer as situation, action, result and it mostly held together, but I fumbled the root cause part.”

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Airbnb·Data Scientist·Technical Phone Screen

May 2026
Airbnb data scientist interview that went deep into metric design and experimentation rigor. The question was essentially one long technical prompt covering everything from logging integrity to power calculations, and it felt less like a conversation and more like defending a thesis.
  • For a newly launched feature, define a primary success metric tied to long-term value. Walk through the exact formula including numerator/denominator definitions, deduplication logic, windowing choices, and how you handle outliers and bot traffic.
  • What are the trade-offs between ratio-of-sums and sum-of-ratios when computing your primary metric, and how does your choice affect sensitivity to late or backfilled events?
  • How would you detect and correct a silent logging change that occurs mid-experiment, and what does timezone misalignment do to your metric computation?
  • Given historical variance from past experiments, compute the minimum detectable effect and required sample size for a 14-day test. Then explain how you'd approach sequential monitoring and alpha spending across that window.
  • Define at least three guardrail metrics for the experiment, set canary thresholds for each, and explain what you'd do if the primary metric improves but one guardrail shows a slight regression.

“This is where I spent most of my time and also where I stumbled first.”

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Airbnb·Software Engineer·Onsite - System Design / Architecture

May 2026
Airbnb system design round, one big meaty question about split-stay search. The kind of problem that sounds manageable until you're actually in it and realize how many edge cases are hiding underneath.
  • Design an HTTP API endpoint that takes a date range and a set of Airbnb listings with their availability, and returns all valid two-listing split-stay combinations where one listing covers the first part of the range and another covers the rest, with no gaps and at most one move between listings.

“This question has a lot of layers and I underestimated how many until I was already mid-explanation.”

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