Katkat

Company

Airbnb interview questions

112 practice questions in the style of Airbnb's interviews, covering Behavioral & Leadership, Data Manipulation (SQL/Python), Coding & Algorithms, Software Engineering Fundamentals, Machine Learning, Analytics & Experimentation, ML System Design, System Design, Statistics & Math.

Questions112

3 easy78 medium31 hard

Your progress0/112

Airbnb interview questions by the numbers

Last updated

Katkat has 112 Airbnb interview questions. The largest topics are Coding & Algorithms (30%), Software Engineering Fundamentals (18%) and Behavioral & Leadership (13%). By difficulty: 3% easy, 70% medium and 28% hard. The most common round is Onsite (45%). Frequent concepts include Data Structures, Design, Greedy and Hash Table.

Difficulty

  • Easy3% · 3
  • Medium70% · 78
  • Hard28% · 31

Interview rounds

  • Onsite45% · 50
  • Technical Screen36% · 40
  • Online Assessment15% · 17
  • HR Screen4% · 4
  • Other1% · 1

Roles

  • Software Engineer67% · 75
  • Data Scientist17% · 19
  • Machine Learning Engineer11% · 12
  • Data Engineer4% · 4
  • Backend Engineer1% · 1

Frequent concepts

  • Data Structures7% · 8
  • Design5% · 6
  • Greedy4% · 5
  • Hash Table4% · 5
  • System Design4% · 5
  • Concurrency4% · 4

Showing 91–112 of 112 results

  • This problem tests your ability to use dynamic programming to determine if a specific target sum can be achieved using a subset of given item values and how to find the minimum subset size that hits that target.

    AirbnbMachine Learning EngineerCoding & AlgorithmsOnsite
  • Tests dynamic programming for the unbounded knapsack/coin change problem, focusing on finding the minimum number of canisters to reach an exact volume and reconstructing the optimal selection.

    AirbnbMachine Learning EngineerCoding & AlgorithmsTechnical Screen
  • Tests a candidate's ability to communicate and defend an end-to-end product A/B test with technical depth, covering hypothesis formulation, experimental design, metric trade-offs, and post-experiment business decisions.

    AirbnbData ScientistBehavioral & LeadershipHR Screen
  • This question evaluates a candidate's ability in product strategy, data-driven user research, metric design, and prioritization within the product/decision-making domain for a consumer mobile application.

    AirbnbSoftware EngineerBehavioral & LeadershipOnsite
  • Design and implement an in-memory timestamped credit ledger that supports deposits, transfers, spending with delayed cashback rewards, account merges, balance queries, and spend rankings.

    AirbnbSoftware EngineerCoding & AlgorithmsOnline Assessment
  • Design a home-search ranker without query text, covering structured intent, training bias, cold start, online evaluation, and production debugging.

    AirbnbMachine Learning EngineerML System DesignOnsite
  • Redact document phrases with a replacement map, whole-word matching, longest-match overlap rules, and one-pass replacement of original text.

    AirbnbMachine Learning EngineerCoding & AlgorithmsOnsite
  • Implement a text formatting utility that wraps multiple paragraphs at distinct per-paragraph widths and renders them inside a single, uniformly padded ASCII border box.

    AirbnbSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates proficiency in Python code review and geolocation data-processing, including competencies in readability, correctness, performance optimization, and architectural scalability.

    AirbnbSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates proficiency in geospatial data processing and Python code review, including detection of correctness bugs, numerical stability issues, CRS handling, performance optimization, refactoring, testing strategy, and security considerations when working with CSV/GeoJSON datasets.

    AirbnbSoftware EngineerData Manipulation (SQL/Python)Technical Screen
  • This problem tests your ability to model a fluid simulation on a grid using a deterministic rule set and efficient array traversal.

    AirbnbSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates proficiency in dynamic programming for coin-change problems and competency in numerical precision and safe handling of decimal monetary values in algorithmic implementations.

    AirbnbMachine Learning EngineerCoding & AlgorithmsOnsite
  • This question evaluates proficiency in linked-list pointer reasoning, cycle detection and shared-reference identification, as well as iterator design for round-robin merging, testing data-structure manipulation, iterator interfaces, and complexity analysis within the Coding & Algorithms domain.

    AirbnbSoftware EngineerCoding & AlgorithmsOnsite
  • Find the minimum moves needed to solve a 2-by-3 sliding puzzle, or report that the target is unreachable. Model each arrangement as a compact graph state, generate legal swaps involving the blank, and use breadth-first search without revisiting configurations.

    AirbnbSoftware EngineerCoding & AlgorithmsOnsite
  • This pair of problems evaluates proficiency with string-processing algorithms and advanced data structures for matching, alongside state-space graph search techniques and state-encoding strategies.

    AirbnbSoftware EngineerCoding & AlgorithmsOnsite
  • A four-level coding assessment that builds an in-memory task management system: adding, updating and retrieving tasks, name search and priority listing, users with quotas and expiring time-based assignments, then task completion and overdue reporting. It tests extensible design, deterministic ordering and time handling.

    AirbnbSoftware EngineerSoftware Engineering FundamentalsOnline Assessment
  • This question evaluates proficiency in statistical inference for A/B testing—estimating and comparing conversion proportions, conducting two-sided hypothesis tests, adjusting for day-level clustering using ICC and design-effect corrections, and performing power and sample-size calculations; it belongs to the Statistics & Math domain for a Data Scientist role and combines conceptual understanding with practical application. It is commonly asked to assess an interviewee's ability to interpret conversion uplift under realistic experimental constraints, account for intra-cluster correlation when estimating effective sample sizes and uncertainty, and reason about experiment duration and robustness checks.

    AirbnbData ScientistStatistics & MathTechnical Screen
  • Implement a timestamped in-memory store of parcel attributes with overwriting set, get and a compare-and-set update, then list attributes as name(value) sorted by name with an optional prefix filter, and finally add per-attribute TTLs that hide expired values. It tests precise operation semantics, expiry rules and incremental class design.

    AirbnbSoftware EngineerSoftware Engineering FundamentalsOnline Assessment
  • Walk through an end-to-end A/B test for an online marketplace feature, covering metric definition, randomization design, SRM diagnosis, and making a launch decision with conflicting trade-offs.

    AirbnbData ScientistAnalytics & ExperimentationHR Screen
  • This question evaluates a software engineer's leadership, project management, technical decision-making, risk mitigation, and ability to quantify business and technical impact through a detailed project walkthrough.

    AirbnbSoftware EngineerBehavioral & LeadershipTechnical Screen
  • This question evaluates a candidate's alignment with organizational values, authenticity of motivation, and ability to articulate personal causes along with concrete actions that demonstrate impact and priorities.

    AirbnbMachine Learning EngineerBehavioral & LeadershipOnsite
  • A four-level coding assessment that builds an in-memory credit ledger for workspaces, much like bank accounts. Levels add deposits, instant transfers with a top-k ranking, scheduled transfers with cancellation, and account merges with historical balance lookups, testing stateful class design, time handling and edge cases.

    AirbnbSoftware EngineerSoftware Engineering FundamentalsOnline Assessment

Airbnb interview experiences

All 25 →
  • Four-Level Parcel Attribute OA, 410/600Airbnb · Software Engineer · Online Assessment · Oct 2026

    The AI-organized question lists I used for the past three months of OAs were basically useless, and I didn't get any repeat questions. It's the same as what people on the forum have been reporting lately: I mass-applied and got the OA instantly. But it's still the 90-minute, four-level format. The problem gives you a batch of Parcels. Each Parcel has its own ParcelId and attributes (key, value),…

  • Auto-Sent CodeSignal OA With a Four-Level Task Management SystemAirbnb · Software Engineer · Online Assessment · Sep 2026

    I mass-applied, and got the OA invite right away. It was probably sent automatically by the system. Standard CodeSignal Industry Coding Assessment. You have to share your screen the entire time and keep your mic on so it picks up audio. The problem I got was a task management system. Level 1: The task management system should support adding, updating and retrieving tasks. Level 2: The task manage…

  • Four-Level Banking System OA, Stuck on Level 3 at 440 PointsAirbnb · Software Engineer · Online Assessment · Sep 2026

    Level 1: Basic banking operations. Needs to support: Level 2: Top Spenders Requirement: rank accounts based on the total value of outgoing transactions Adds something like: Level 3: Scheduled Payments. The system needs to support: schedule payment accept payment The biggest trap here is the timestamp execution order. It's not just "store a record when schedule_payment is called" and that's it. Ev…

  • Four-Round Onsite, Then a Recruiter Who Ghosted MeAirbnb · Data Engineer · Onsite · Sep 2026
    Rejected

    Not many interview reports out there, so let me add mine — hope it helps. My recruiter was unreliable and ghosted me right after the interview. One round of OA. The VO (onsite) was four rounds of analytics interviews. OA: The SQL was pretty easy. The Python question gave a list/dict of city housing prices, and I had to find the median price for each city. VO: SQL: Find the top N, then figure out…

  • Search Ranking and Team MatchingAirbnb · Machine Learning Engineer · Senior+ · Onsite · Sep 2026

    A referred applicant to Airbnb’s personalization and relevance organization reports recruiter contact after two weeks. An initial coding screen asked for book titles to be formatted as a table. Four days later, the applicant advanced to a virtual onsite covering document redaction, project decisions, search ranking without text queries, and retrieval-assisted guidance for customer-support staff.…

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