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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 3331–3360 of 3640 results
- TikTokHardData ScientistTest 15s to 60s video length change
This question evaluates a data scientist's competency in experimental design, causal inference, metric definition and instrumentation, power/MDE calculations, interference and contamination handling on multi‑sided platforms, and rollout planning.
Analytics & ExperimentationOnsite - TikTokEasyData ScientistTest Billboard Campaign Conversion Rate Exceeds 60%
Evaluates one-sample proportion testing for a billboard conversion rate with 65 conversions out of 100 users. Strong answers state one-sided hypotheses, compute the standard error and confidence interval, run the correct z test against 60%, and interpret why statistical evidence may be insufficient.
Statistics & MathOnsite - TikTokHardMachine Learning EngineerWalk through resume under pressure and critique
A TikTok machine-learning-engineer onsite behavioral & leadership question: walk through four resume projects — problem and constraints, your ownership, architecture and key decisions, alternatives and trade-offs, measurable outcomes, and the hardest challenge — then defend your trade-offs under pushback, respond to blunt feedback, and adapt your communication to a different language or style. It evaluates technical ownership, systems thinking, experimental rigor, and composed, data-first communication under pressure.
Behavioral & LeadershipOnsite - TikTokMediumData ScientistWrite SQL for geo posting-frequency drops
This question evaluates proficiency in SQL-based time-series data manipulation, including time zone–aware date normalization, window functions, aggregation, filtering and median computations within the Data Manipulation (SQL/Python) domain.
Data Manipulation (SQL/Python)Onsite - TinderHardProduct ManagerProfile Customization for Millennials & Gen Z
Practice designing a Tinder profile-customization feature for Millennials and Gen Z without slowing the swipe experience. The solution proposes modular Profile Layers, explains cohort needs, safety and moderation constraints, research validation, launch sequencing, and metrics for match quality, conversations, retention, and guardrails.
Product / Decision MakingOnsite - TradedeskMediumFrontend EngineerDebug a Frontend Component That Shows Wrong API Results
A front-end debugging question in which a React component that fetches data sometimes shows results that do not match the current input, even though each API response is correct. It tests how the candidate reproduces a timing-dependent bug, finds the root cause, fixes it in the effect, handles cancellation errors, and verifies the fix with a deterministic test.
Software Engineering FundamentalsOnsite - TradedeskMediumFrontend EngineerImplement a Publish-Subscribe Event Bus in JavaScript or TypeScript
A front-end coding question asking the candidate to implement an in-process publish-subscribe utility in JavaScript or TypeScript with subscribe, publish, and unsubscribe. It tests API design, choice of data structures, safe iteration when subscribers change during a publish, isolation of subscriber errors, and cleanup that avoids memory leaks.
Software Engineering FundamentalsOnsite - TradedeskMediumFrontend EngineerObject-Oriented Design of an Elevator Control System
An object-oriented design question asking the candidate to model an elevator control system: its classes, their responsibilities, and how a button press becomes an elevator stop. It tests requirement scoping, a clear per-car state model, stop ordering and dispatch policies that can be swapped out, handling of out-of-service cars and duplicate requests, and testability.
Software Engineering FundamentalsOnsite - TrexquantMediumSoftware EngineerImplement Trie search with wildcard matching
This question evaluates understanding of trie data structures, string pattern matching with wildcard characters, and efficient algorithm design for large-scale add/search operations.
Coding & AlgorithmsOnsite - TrexquantMediumSoftware EngineerMaintain median of a data stream
This question evaluates proficiency in streaming data aggregation, dynamic order-statistics maintenance, and algorithmic complexity analysis for insertion and query operations.
Coding & AlgorithmsOnsite - TruefoundryMediumSoftware EngineerDesign Interviewer Availability and Atomic Booking APIs
Design a relational data model and concurrent APIs for managing interviewer availability and atomic candidate interview booking.
System DesignOnsiteConcurrencyDatabase DesignAPI Design - TruefoundryMediumSoftware EngineerQuery a Versioned Array
This problem tests your ability to design a data structure that supports efficient state snapshots and point queries, specifically focusing on space-time trade-offs.
Coding & AlgorithmsOnsiteData StructuresBinary SearchArrays - TruefoundryMediumSoftware EngineerVerify Ordering Under a Scrambled Alphabet
This problem tests string manipulation, hash map usage for indexing, and the ability to compare two strings based on custom character priority.
Coding & AlgorithmsOnsiteStringsSortingHash Map - TuroHardData ScientistCompare XGBoost and LightGBM
This question evaluates a data scientist's understanding of gradient-boosted tree implementations and practical model trade-offs, covering competencies in algorithmic differences, performance and memory characteristics, handling of missing and categorical features, regularization risks, and hyperparameter considerations for production models.
Machine LearningOnsite - TuroHardData ScientistIdentify Booking Drivers
This question evaluates skills in product analytics, causal inference, feature importance modeling, metric definition, and experimental validation within a marketplace context.
Analytics & ExperimentationOnsite - TwitchMediumSoftware EngineerSolve four design-leaning coding problems
This multi-part question evaluates algorithmic problem-solving, data structure design and manipulation (such as LRU cache semantics), stateful simulation and scoring logic, chronological quota accounting for billing, and set/map operations for detecting overlaps.
Coding & AlgorithmsOnsite - Two SigmaHardData ScientistBuild a Housing Price Prediction Model from Historical Data
This question evaluates a data scientist's competency in end-to-end supervised machine learning for real-estate pricing, focusing on precise outcome definition, feature engineering, handling missing and time-varying data, and robustness to market regime changes.
Machine LearningOnsite - Two SigmaHardData ScientistCount Distinct Island Shapes in a Binary Grid
This question evaluates a candidate's understanding of grid-based connected components and spatial equivalence, measuring competency in representing and distinguishing island shapes regardless of their location.
Coding & AlgorithmsOnsite - Two SigmaMediumSoftware EngineerExplain move and recent project
This interview question evaluates behavioral evidence, ownership, communication, trade-offs, and measurable outcomes in a realistic interview setting. A strong answer for Explain move and recent project states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Behavioral & LeadershipOnsite - Two SigmaHardSoftware EngineerHow to prepare for a hiring manager round
This question evaluates behavioral and leadership competencies such as past project execution, collaboration, communication, decision-making, and role fit beyond coding and technical screens.
Behavioral & LeadershipOnsite - Two SigmaHardData ScientistImplement Univariate Linear Regression with Ordinary Least Squares
This question evaluates understanding of univariate linear regression and the ordinary least squares (OLS) closed-form estimator, probing competencies in basic statistical estimation, interpretation of slope and intercept, numerical stability, and floating-point arithmetic.
Coding & AlgorithmsOnsite - Two SigmaHardData ScientistMaximum-Product Simple Path in a Complete Directed Graph
This question evaluates skills in graph algorithms, multiplicative path optimization, and combinatorial dynamic programming, testing competency in reasoning about simple paths and product-based scoring in directed weighted graphs.
Coding & AlgorithmsOnsite - Two SigmaMediumSoftware EngineerSolve capital selection and grid escape
This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Solve capital selection and grid escape states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Coding & AlgorithmsOnsite - UberMediumSoftware EngineerAligning Two Teams with Conflicting Priorities and Learning from a Mistake
Two senior behavioral prompts: describe bringing two teams with conflicting priorities into alignment to deliver an important project, and a mistake you made, the feedback you received and how you closed the gap. It assesses cross-team influence, conflict resolution and growth.
Behavioral & LeadershipOnsite - UberMediumSoftware EngineerAnswer Common Behavioral Questions
This question assesses the candidate's ability to navigate professional conflict and technical disagreements while maintaining constructive relationships and project momentum.
Behavioral & LeadershipOnsiteBehavioralConflict ResolutionLeadership - UberHardSoftware EngineerAnswer Repeated Shortest Increasing-Path Queries
Preprocess shortest strictly increasing grid paths for repeated target queries, with deterministic BFS ties, predecessor reconstruction, and memory trade-offs.
Coding & AlgorithmsOnsite - UberMediumMachine Learning EngineerAnswer leadership questions on tradeoffs and collaboration
This set of behavioral leadership questions evaluates leadership competencies including trade-off decision-making, mentorship, cross-functional collaboration, roadmap prioritization, and conflict resolution for a Machine Learning Engineer within the Behavioral & Leadership domain, focusing on practical application through recounting real project experiences. These prompts are commonly asked to probe both conceptual understanding of trade-offs and organizational dynamics and the practical application of influence, communication, and judgment when aligning stakeholders and prioritizing work.
Behavioral & LeadershipOnsite - UberMediumSoftware EngineerAssign Meetings to the Minimum Number of Rooms
Assign meetings to the minimum number of rooms using deterministic room ID allocation, returning the room assigned to each meeting in original input order.
Coding & AlgorithmsOnsiteheapintervalssorting - UberMediumSoftware EngineerBehavioral: your most complex project, a conflict you resolved, and a failure
Three hiring-manager behavioral questions: describe your most complex project, a conflict you resolved, and a failure you owned. Answers are judged on STAR structure, personal ownership, concrete and measurable results, a fair account of other people's views, and lessons that were actually applied later.
Behavioral & LeadershipOnsite - UberHardSoftware EngineerBuild Quadtree and Find Grid Words
This problem tests your ability to implement a spatial partitioning data structure (Quadtree) for a grid and perform recursive searches to locate words within that grid efficiently.
Coding & AlgorithmsOnsiteQuadtreeBacktrackingTrie
TikTok
Tradedesk
Trexquant
Turo
Twitch
Two Sigma
Uber