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Interview Questions
Practice 9403 coding, system design and machine learning questions from 546 companies, sorted by role, topic and interview round. Every question has step-by-step hints, a code runner that supports 8 languages and an AI mentor; members also get the full solution walkthrough.
- 9403
- Questions
- 546
- Companies
- 11
- Topics
- 8
- Languages
Showing 61–90 of 4616 results
- Aim Intelligent MachineMediumSoftware EngineerMerge Overlapping Closed Intervals into a Sorted Disjoint List
Tests sorting and linear scanning techniques to merge overlapping closed intervals, with attention to shared boundaries, nested ranges, and large input scale.
Coding & AlgorithmsTechnical ScreenIntervalsSortingArray - AirbnbMediumSoftware EngineerAddress miscommunication and alignment
Address miscommunication and alignment evaluates behavioral evidence, ownership, communication, trade-offs, and measurable outcomes in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Behavioral & LeadershipTechnical Screen - AirbnbMediumData ScientistAggregate User Activity, Fit Regression, Interpret Coefficients
This question evaluates skills in relational data aggregation and feature engineering using SQL alongside fitting and interpreting regression models in Python, targeting competencies in transforming event-level user metrics into a modeling dataset and interpreting coefficient estimates.
Data Manipulation (SQL/Python)Technical Screen - AirbnbHardSoftware EngineerAnswer cross-team delivery and values questions
This question evaluates a candidate's competency in cross-team delivery, stakeholder communication across time zones and cultures, project ownership, risk assessment, and leadership when internal ETAs slip, and it falls under the Behavioral & Leadership category.
Behavioral & LeadershipTechnical Screen - AirbnbMediumData ScientistBuild and evaluate an order prediction model
This question tests the ability to design a robust end-to-end machine learning pipeline for binary classification, focusing on preventing temporal data leakage, managing class imbalance, and aligning model thresholds with business objectives.
Machine LearningTechnical ScreenClassificationTemporal LeakageModel Evaluation - AirbnbMediumData ScientistBuild panel in SQL; run causal regression
This question evaluates proficiency in SQL-based panel data construction, time-series aggregation and rolling-window metrics together with applied causal inference in Python, including two-way fixed-effects difference-in-differences, clustered standard errors, lead tests, and count-model re-specification; it targets Data Manipulation (SQL/Python) skills relevant for Data Scientist roles. It is commonly asked because it combines practical implementation and conceptual understanding—testing temporal joins, treatment timing, avoidance of lookahead/immortal-time biases and late-adopter issues, interpretation of interaction coefficients and confidence intervals, and the ability to reason about identification and model choice.
Data Manipulation (SQL/Python)Technical Screen - AirbnbMediumData ScientistCompute C/T metrics from bookings and visits
This question evaluates time-window attribution, visit deduplication, control vs treatment metric computation, aggregation of conversions and revenue, and statistical interval estimation (Wilson CIs), testing practical data manipulation skills with SQL or Python in the Data Manipulation (SQL/Python) domain.
Data Manipulation (SQL/Python)Technical Screen - AirbnbMediumData ScientistCompute browsing metrics in Python from logs
This question evaluates a candidate's ability to perform event-level data manipulation and analytics in Python and SQL, covering sessionization, time-zone–consistent timestamp handling, deduplication, funnel construction, segment-level aggregation, conversion-rate computation, and statistical confidence intervals such as the Wilson CI.
Data Manipulation (SQL/Python)Technical Screen - AirbnbMediumSoftware EngineerCompute minimum-cost service cover
This question evaluates proficiency in combinatorial optimization and set-coverage with cost minimization, including handling case-insensitive service matching and enumerating minimal solution combinations.
Coding & AlgorithmsTechnical Screen - AirbnbMediumSoftware EngineerCompute split-stay listing pairs
This question evaluates the ability to manipulate interval availability data, reason about contiguous date ranges and split boundaries, and design efficient pairing algorithms with attention to time and space complexity.
Coding & AlgorithmsTechnical Screen - AirbnbMediumSoftware EngineerConstruct smallest number from I/D pattern
This problem tests greedy algorithm design and stack-based data structure manipulation to satisfy relative ordering constraints within a sequence of digits.
Coding & AlgorithmsTechnical ScreenGreedyStackStrings - AirbnbMediumSoftware EngineerCount Candies from Unlockable Boxes
Determine the maximum number of candies you can collect given an initial set of boxes, where each box may be locked or unlocked, contain candies, contain keys to other boxes, and contain other boxes.
Coding & AlgorithmsTechnical ScreenBreadth-First SearchGraphQueue - AirbnbMediumData ScientistDefine Success Metrics and Experiment Plan for Product Development
Evaluates product-planning metrics and experiment design for a two-sided marketplace booking funnel. Strong answers define a primary booking metric, diagnostic and guardrail metrics, randomization unit, sample size, marketplace spillovers, and launch criteria before development.
Analytics & ExperimentationTechnical Screen - AirbnbMediumSoftware EngineerDesign a banking ledger for deposits/withdrawals
This question tests your ability to design a robust database schema and service logic for a banking system, focusing on data integrity, transaction atomicity, and handling high-concurrency balance updates.
Software Engineering FundamentalsTechnical ScreenDatabase DesignConcurrencyTransactions - AirbnbHardSoftware EngineerDesign a fast host listing metrics page
This question evaluates backend system design and data engineering competencies, including scalable API design, time-range aggregation correctness (handling partial overlaps and state changes), data modeling and indexing, caching and precomputation, and performance validation.
System DesignTechnical Screen - AirbnbHardSoftware EngineerDesign a multi-channel notification system
This question tests the ability to design a distributed, multi-channel notification system capable of handling high throughput, varying latency requirements across channels (e.g., email, push, SMS), and ensuring reliable message delivery.
System DesignTechnical ScreenDistributed SystemsScalabilityMessage Queues - AirbnbMediumData ScientistDesign a network-aware Wi‑Fi badge experiment
This question evaluates a data scientist's proficiency in experimental design, causal inference under interference (including SUTVA risks), metric specification, power and sample‑size computation, analysis planning, and translating treatment effects into financial decision rules.
Analytics & ExperimentationTechnical Screen - AirbnbHardData ScientistDesign an A/B test with causal inference
This question evaluates skills in experimental design, causal inference, and applied statistics — including estimand selection, sample-size calculation under clustering, integrity monitoring, handling noncompliance and contamination, sequential monitoring, and two-proportion inference — within the Analytics & Experimentation domain for a Data Scientist role. It is commonly asked because interviewers need to assess the ability to design and analyze robust A/B tests under real-world constraints; the prompt requires both conceptual understanding of causal assumptions and practical application of power calculations, diagnostics, and monitoring procedures.
Analytics & ExperimentationTechnical Screen - AirbnbHardSoftware EngineerDesign an Airbnb wallet with holds and payouts
This question evaluates a candidate's competency in designing financial transaction systems, covering double-entry append-only ledgers, holds/authorizations and captures, refunds and payouts, multi-currency FX conversion and rounding, idempotency, concurrency safety, and auditable reconciliation.
System DesignTechnical Screen - AirbnbMediumSoftware EngineerDesign an extensible request Retryer
This question evaluates a candidate's ability to design extensible and robust retry mechanisms, covering competencies in API/interface design, fault tolerance, backoff and jitter strategies, cancellation/deadline handling, idempotency considerations, and observability.
Software Engineering FundamentalsTechnical Screen - AirbnbMediumData ScientistDesign and Analyze Airbnb Locker Experiment
This question evaluates a candidate's skills in experimental design and causal inference for marketplace features, including selecting the appropriate randomization unit, defining eligibility and treatment/control arms, and choosing primary, secondary, and guardrail metrics.
Analytics & ExperimentationTechnical Screen - AirbnbMediumSoftware EngineerDesign and implement Connect Four engine
This question evaluates a candidate's competency in algorithmic problem solving, data structure selection, API design, complexity analysis, and testing through implementation of a Connect Four game engine.
Coding & AlgorithmsTechnical Screen - AirbnbMediumSoftware EngineerDesign and implement an Airbnb wallet
This question evaluates system design and object-oriented design skills focused on transactional accounting, escrow-based payment flows, idempotency, and robust error handling, plus the ability to produce a runnable in-memory implementation.
System DesignTechnical Screen - AirbnbHardData ScientistDesign robust primary and guardrail metrics
This question evaluates proficiency in experiment metric design, guardrail definition, data quality diagnostics, and statistical analysis for A/B testing, including power calculations and sequential monitoring, within the Analytics & Experimentation domain.
Analytics & ExperimentationTechnical Screen - AirbnbMediumSoftware EngineerDetermine Exact Layover Booking
Determine if a subset of layover activities can be booked such that their total cost exactly matches a target voucher balance, handling floating-point currency without precision loss.
Coding & AlgorithmsTechnical ScreenDynamic ProgrammingBacktrackingSubset Sum - AirbnbMediumSoftware EngineerDiscuss learning and feedback experiences
This interview question evaluates behavioral evidence, ownership, communication, trade-offs, and measurable outcomes in a realistic interview setting. A strong answer for Discuss learning and feedback experiences states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Behavioral & LeadershipTechnical Screen - AirbnbHardData ScientistEstimate Causal Impact Using Synthetic Control Methods
Evaluates causal impact estimation after a full product rollout with no holdout. Strong answers use interrupted time series, synthetic control, Bayesian structural time series, exposure variation, and placebo tests to build and validate a credible counterfactual.
Analytics & ExperimentationTechnical Screen - AirbnbHardData ScientistEstimate impact of global launch without holdout
This question evaluates a candidate's competence in causal inference, observational study design, and statistical uncertainty quantification for product analytics, specifically estimating lift after a global launch without a holdout while addressing confounding, interference, and operational data-quality issues.
Analytics & ExperimentationTechnical Screen - AirbnbMediumSoftware EngineerExplain why you want to join Airbnb
This question evaluates a software engineer's ability to articulate authentic motivation, product literacy, and cultural fit in a values-focused interview round. It tests how well candidates can connect their engineering background to real organizational problems and communicate genuine alignment — skills commonly assessed in the culture and behavioral rounds of technical interview loops.
Behavioral & LeadershipTechnical Screen - AirbnbMediumSoftware EngineerFind minimal property set in neighborhood
This question evaluates combinatorial optimization and algorithm design skills, focusing on capacity-constrained selection (subset-sum/knapsack-style reasoning), deterministic tie-breaking, and complexity analysis within the Coding & Algorithms domain.
Coding & AlgorithmsTechnical Screen
Airbnb