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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
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- 11
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Showing 2131–2160 of 3640 results
- MetaMediumMachine Learning EngineerMaximize unique characters from a word list
This problem tests your ability to use recursion with backtracking or bitmasking to find the optimal subset of strings that maximize the total count of unique characters.
Coding & AlgorithmsOnsiteBacktrackingBitmaskingRecursion - MetaMediumData ScientistMeasure a friend-recommendation launch
This question evaluates experiment design, metric selection, causal inference and business-metric translation for social features, including defining primary and guardrail metrics, choosing experimental units to mitigate network interference, and estimating revenue impact from observed lifts.
Analytics & ExperimentationOnsite - MetaHardData ScientistMeasure impact of bot mitigation via experiment
This question evaluates experiment design and causal inference skills for platform analytics, covering interference management, metric and guardrail definition, power and duration calculations, eligibility and exclusions, novelty/adaptation considerations, and diagnostics for bot‑mitigation interventions.
Analytics & ExperimentationOnsite - MetaMediumData ScientistMeasure scheduled posts feature success
This question evaluates proficiency in Bayesian statistical estimation, experimental design, product metric definition, and causal/confounder analysis for measuring feature reliability and engagement.
Analytics & ExperimentationOnsite - MetaMediumSoftware EngineerMerge Two Lists of Non-Overlapping Intervals
This question evaluates a candidate's ability to merge two pre-sorted, non-overlapping interval lists into a single consolidated set, a core array and two-pointer/merging skill in coding interviews. It tests correct handling of edge cases like touching endpoints versus true gaps, assessing precision in interval logic and algorithmic reasoning under linear-time constraints.
Coding & AlgorithmsOnsite - MetaMediumSoftware EngineerMerge overlapping intervals
This problem tests your ability to manipulate array-based data by sorting and performing linear sweeps to consolidate overlapping ranges.
Coding & AlgorithmsOnsiteArraysSortingGreedy - MetaHardProduct ManagerMeta PM Interview Questions
Practice a mixed PM onsite loop with strategy, data, product design, architecture, analytics, technical leadership, and failure reflection prompts. The solution guide shows how to structure each case, ask clarifying questions, choose metrics, make trade-offs, and give practical recommendations.
Product / Decision MakingOnsite - MetaMediumProduct ManagerMeta Pay: Metrics & Prioritization
Practice Meta Pay PM metrics and prioritization with North Star definition, metric tree, split-bill versus donations trade-offs, and debugging flat adoption despite lower cost per transaction. The solution covers active payers, transaction success, trust, risk, unit economics, feature strategy, and decomposition analysis.
Product / Decision MakingOnsite - MetaMediumSoftware EngineerMinimum Round-Trip Flight Cost
This question evaluates a candidate's ability to optimize over paired sequences using array traversal and running-minimum tracking, a core array-processing technique in coding interviews. It tests practical application of single-pass optimization under an ordering constraint rather than brute-force pairwise comparison, commonly used to assess algorithmic efficiency and edge-case handling.
Coding & AlgorithmsOnsite - MetaMediumData ScientistModel session times and comments with exponential/Poisson
This question evaluates understanding of memoryless processes and count-data modeling, covering exponential (constant-hazard) distributions for session durations and Poisson approximations for comment counts within survival analysis and count-data modeling in Statistics & Math for a Data Scientist role.
Statistics & MathOnsite - MetaMediumSoftware EngineerMove Work Forward Across Teams
This question evaluates your ability as a senior engineer to drive cross-functional alignment, manage complex technical dependencies, and deliver impact across multiple teams with competing priorities.
Behavioral & LeadershipOnsiteBehavioralCross-Team CollaborationLeadership - MetaHardSoftware EngineerNavigate Stakeholder Conflict During a Compressed Delivery Timeline
Describe a project where a deadline moved earlier and stakeholders disagreed about what should ship. Explain how you exposed the conflict, tested a failing approach, incorporated senior feedback, changed course, and used a concrete result to assess the compromise.
Behavioral & LeadershipOnsite - MetaMediumData ScientistOptimize Oculus Data Streaming with Bandwidth Constraints
This question evaluates a candidate's ability in algorithm design and problem decomposition for array segmentation and interval coverage, focusing on reasoning about cumulative constraints for streaming data and geometric interval intersections.
Coding & AlgorithmsOnsite - MetaHardMachine Learning EngineerOptimize a Fifteen-Sum Card Strategy
This problem tests your ability to optimize a combinatorial search space through memoization and dynamic programming to determine the maximum win rate of a card-based strategy.
Coding & AlgorithmsOnsiteCombinatoricsProbabilityRecursion - MetaMediumMachine Learning EngineerOptimize ribbon piece length by binary search
This question evaluates understanding of binary-search-on-answer techniques and monotonic predicates, complexity analysis, and implementation-level handling of integer overflow and extreme edge cases in numeric partitioning, situated in the coding and algorithms domain and emphasizing practical implementation considerations rather than purely theoretical proofs. It is commonly asked because it reveals whether an interviewee can reason about monotonicity and design an O(n log max(lengths)) solution that remains robust under very large k, large element values, and potential integer overflow.
Coding & AlgorithmsOnsite - MetaMediumSoftware EngineerPrepare answers for core behavioral questions
This question set evaluates interpersonal and leadership competencies such as communication, conflict resolution, giving and receiving feedback, problem-solving, ownership, handling ambiguity, and the ability to articulate measurable impact and self-awareness.
Behavioral & LeadershipOnsite - MetaMediumProduct ManagerProgram Execution Deep Dive
Practice a Product Manager program execution deep dive covering requirements capture, prioritization, stakeholder conflict, risk mitigation, launch planning, staged rollout, metrics, guardrails, and post-launch learning.
Product / Decision MakingOnsite - MetaMediumData ScientistPromote Inclusion and Overcome Barriers in Social-Commerce Team
Promote Inclusion and Overcome Barriers in Social-Commerce Team 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 - MetaHardData ScientistProve source growth is cannibalization, not incremental
This question evaluates causal inference and experimental-design competencies in analytics, testing skills in identification strategy, treatment and control definition, specification of difference‑in‑differences or randomized geo experiments, metric construction, power calculations, and robustness checks for attribution and cannibalization analysis. It is commonly asked to determine whether observed growth is incremental or substitution-driven, falls under the Analytics & Experimentation domain in Data Science, and emphasizes practical application accompanied by conceptual understanding of identification assumptions, statistical power, and measurement.
Analytics & ExperimentationOnsite - MetaMediumData ScientistRank Ads by Conversion Rate for Top 10 Performers
This question evaluates data manipulation and analytics skills for computing time-windowed ad performance metrics, including aggregations of impressions and revenue, join logic between impression and conversion records, conversion-rate calculation, and ranking.
Data Manipulation (SQL/Python)Onsite - MetaMediumData EngineerRecommend two-hop follows in Python
This question evaluates fluency with graph traversal, set operations, deduplication, and frequency-based ranking in Python, targeting manipulation of directed "follows" relationships represented as dictionaries and is categorized under Data Manipulation (SQL/Python).
Data Manipulation (SQL/Python)Onsite - MetaMediumData ScientistRedesign an executive dashboard for C-suite
This question evaluates skills in dashboard design, data visualization, metric selection, and executive-level analytical communication for product and growth measurement.
Analytics & ExperimentationOnsite - MetaMediumData ScientistReduce variance with covariate adjustment
This question evaluates a data scientist's competency in experimental design, variance reduction techniques, and regression-based covariate adjustment (CUPED/ANCOVA) within randomized A/B tests, including understanding of statistical power and diagnostic checks.
Analytics & ExperimentationOnsite - MetaMediumData ScientistReflect on Conflict Resolution and Key Learnings
This interview question evaluates behavioral evidence, ownership, communication, trade-offs, and measurable outcomes in a realistic interview setting. A strong answer for Reflect on Conflict Resolution and Key Learnings states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Behavioral & LeadershipOnsite - MetaHardData ScientistReplace legacy ads model safely
This question evaluates competence in machine learning systems engineering, including offline validation, counterfactual/off‑policy evaluation, online experimentation design, and production monitoring for ad-ranking models.
Machine LearningOnsite - MetaHardSoftware EngineerResolve Ambiguous Requirements Before Building
Tests your ability to drive clarity and make responsible engineering progress when assigned a critical project with underspecified or conflicting requirements.
Behavioral & LeadershipOnsiteBehavioralRequirements AmbiguityStakeholder Alignment - MetaMediumData ScientistResolve Conflicts and Convince Skeptical Stakeholders Effectively
This interview question evaluates behavioral evidence, ownership, communication, trade-offs, and measurable outcomes in a realistic interview setting. A strong answer for Resolve Conflicts and Convince Skeptical Stakeholders Effectively states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Behavioral & LeadershipOnsite - MetaMediumData ScientistResolve Ties for Top-10 Users in SQL Query
This question evaluates proficiency in SQL ranking and tie-resolution techniques for generating deterministic top-N leaderboards, focusing on handling identical scores while producing an exact set of rows.
Data Manipulation (SQL/Python)Onsite - MetaMediumSoftware EngineerResolve a cd Path Against the Current Directory
Implement simplified Unix-style cd path resolution for absolute and relative inputs containing repeated separators, dot components, and parent-directory steps. The challenge focuses on component semantics, root boundaries, empty arguments, exact normalization, and linear processing of long paths without filesystem lookups.
Coding & AlgorithmsOnsite - MetaMediumData ScientistResolve cross-team conflict and align incentives
This question evaluates a Data Scientist's ability to resolve cross-team conflicts through stakeholder mapping, incentive alignment, quantified negotiation planning, meeting facilitation, escalation management, and success measurement.
Behavioral & LeadershipOnsite
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