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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.
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Showing 91–120 of 9403 results
- AffirmMediumSoftware EngineerDiscuss team fit and leadership with manager
Discuss team fit and leadership with manager 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 & LeadershipOnsite - AffirmMediumSoftware EngineerExplain Why This Company and Role Interest You
This question assesses the candidate's research into the company's business model (BNPL), their alignment with financial technology values, and their ability to articulate a clear value proposition for the engineering role.
Behavioral & LeadershipHR ScreenBehavioralFintechCareer Alignment - AffirmMediumSoftware EngineerExplain Your Role Motivation, Technical Fit, and Engineering Leadership
This prompt evaluates your ability to deliver a clear, structured narrative during an initial recruiter screen, connecting your technical background, reasons for moving, and fintech/platform motivation to a concrete leadership achievement.
Behavioral & LeadershipHR ScreenBehavioralCareer NarrativeLeadership - AffirmMediumSoftware EngineerFind shortest unique substring per word
This problem tests your ability to manipulate string data structures (like Tries or Suffix Trees) to efficiently identify the shortest, lexicographically smallest substring that is unique to a given word within a provided collection.
Coding & AlgorithmsTechnical ScreenStringsTrieHash Map - AffirmMediumSoftware EngineerHiring Manager Behavioral Interview: Challenging Project, Deadlines, Cross-Team Work
A hiring manager asks you to introduce yourself, describe a challenging project, explain why you want to join Affirm, and discuss delivering under a tight timeline, working across teams and finding where a system needs improvement. It tests structured, evidence-based behavioral answers and engineering judgment.
Behavioral & LeadershipTechnical Screen - AffirmEasySoftware EngineerImplement an LRU cache
This question tests the ability to combine a hash map and a doubly linked list to achieve constant-time performance for both data retrieval and update operations in a cache.
Coding & AlgorithmsOnsiteHash MapLinked ListDesign - AffirmMediumSoftware EngineerImplement and debug event filtering in Python
This question evaluates proficiency in data manipulation and algorithmic reasoning in Python, covering event filtering, stable sorting, deduplication by identifier, timestamp windowing, and analysis of time and space complexity.
Data Manipulation (SQL/Python)Onsite - AffirmMediumData AnalystInvestigate Rising Loan Delinquency with Stable Approval Rates
Diagnose rising 30-day loan delinquency, separate borrower-mix shifts from model drift, and evaluate merchant underwriting changes.
Analytics & ExperimentationTechnical Screen - AffirmMediumData AnalystInvestigate a Quarterly Increase in Loan Delinquency
Investigate rising delinquency through rate definitions, reporting checks, loan vintages, seasoning, portfolio mix, and within-segment deterioration.
Analytics & ExperimentationTechnical Screen - AffirmMediumData AnalystPresent a Relevant Analytics Project to a Hiring Manager
This question tests your ability to structure a past data project using the STAR method, with a specific focus on technical rigor, business logic, and self-reflection.
Behavioral & LeadershipTechnical ScreenBehavioralAnalyticsStorytelling - AffirmHardSoftware EngineerSimulate a High-Card Deck Game for Two Players, Then N Players
Model a shuffled 52-card game in which each round the higher top card wins both cards, then report the player with the most cards won. Starts with two players and generalizes to N players with uneven round-robin dealing, testing object design, rule clarification, and deterministic tests.
Software Engineering FundamentalsTechnical Screen - AgodaMediumSoftware EngineerCompute probability two arrivals meet within 15 minutes
This question evaluates understanding of continuous probability and geometric probability, focusing on independent uniform random variables and reasoning about time-window overlap.
Software Engineering FundamentalsTechnical Screen - AgodaMediumSoftware EngineerCompute triangle min path and dice stopping stats
This composite question evaluates dynamic programming and algorithmic optimization via the triangle minimum path problem and probability, stopping-time analysis and Monte Carlo simulation through the two-dice experiment, testing competencies in DP, discrete probability, expected-value reasoning and empirical estimation.
Coding & AlgorithmsTechnical Screen - AgodaEasyData EngineerCount Integers That Appear Exactly Once
Count distinct integers with frequency exactly one using complete occurrence counts, including empty arrays and separated duplicates.
Coding & AlgorithmsTechnical Screen - AgodaEasyData EngineerFind the Longest Calendar-Day Streak with All Employees Present
Identify dates when every employee is present and compute the longest consecutive streak, treating missing attendance as a gap.
Data Manipulation (SQL/Python)Technical Screen - AgodaMediumSoftware EngineerFind two numbers that sum to a target
This question evaluates array manipulation, index-based reasoning, and algorithmic problem-solving skills related to identifying value pairs that meet a numeric target.
Coding & AlgorithmsTechnical Screen - AgodaEasyData EngineerRank Customers by Monthly Revenue with Competition Ties
Aggregate customer revenue by month and return top competition ranks, preserving tied totals and deterministic display order.
Data Manipulation (SQL/Python)Technical Screen - AgodaEasyData EngineerReturn Every Employee with a Mapped or Default Unique ID
Join employees to unique-ID mappings while preserving unmatched employees and applying an explicit fallback identifier.
Data Manipulation (SQL/Python)Technical Screen - Ai2MediumSoftware EngineerMaintain an Out-of-Order Step Progress Tree
This problem tests tree reconstruction from a stream of out-of-order parent-child updates, requiring efficient hierarchical state management and cycle detection.
Coding & AlgorithmsTechnical ScreenTreesGraphsData Structures - 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 - AirbnbMediumProduct ManagerAirbnb Mission, Belonging & Hosting
Practice Airbnb behavioral interview answers about mission, belonging, hosting, and product empathy. The guide connects Airbnb's mission to personal stories, inclusive team behavior, guest and host trust, safety, accessibility, hosting concepts, and measurable product impact.
Behavioral & LeadershipOther - AirbnbMediumSoftware EngineerAllocate an Order from the Oldest Inventory Batches
Implement a function to allocate an order across inventory batches using FIFO (oldest timestamp first, with batch ID tie-breaker), returning allocation details and any unfilled quantity without mutating the input.
Coding & AlgorithmsOnsitesortinggreedyarrays - AirbnbMediumSoftware EngineerAllocate refund across payments
This question evaluates algorithm design and data-structure selection skills, focusing on greedy allocation, ordering by priority and recency, aggregation of transaction amounts, and analysis of time complexity.
Coding & AlgorithmsOnsite - 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 - AirbnbMediumSoftware EngineerBuild an Incremental Loyalty-Points Ledger with Scheduled, Cancelable Transfers
Implement an in-memory loyalty-points ledger that grows in three stages: atomic transfers between accounts, transfers scheduled for a future point on a simulated clock, and cancellation of a transfer before it fires. Tests incremental state-machine design, validating before mutating, and keeping point totals correct across every sequence of calls.
Software Engineering FundamentalsOnline Assessmentstate-machineoopsimulation - 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 EngineerCalculate the Median House Price in Each City
Tests your ability to compute grouped medians in PostgreSQL, properly handling even and odd row counts, duplicate price values, and numeric precision.
Data Manipulation (SQL/Python)Onsitesqlpostgresqlaggregations
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