Katkat

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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 121–150 of 263 results

  • ImcMediumSoftware Engineer
    Answer conceptual true/false and caching questions

    This problem tests foundational knowledge of computer architecture (integer representation), memory management strategies (caching), and graph theory essentials.

    Software Engineering FundamentalsHR ScreenFundamentalsComputer ArchitectureCaching
  • ImcMediumData Scientist
    Managing a Research Project End to End

    This question assesses a candidate's ability to structure open-ended research, manage stakeholder expectations, and maintain scientific rigor while ensuring the final output is actionable for a business audience.

    Behavioral & LeadershipHR ScreenProject ManagementCommunicationAmbiguity
  • ImcMediumData Scientist
    Motivation for Quantitative Research

    This question assesses the candidate's ability to articulate their intellectual passion for quantitative research by connecting personal motivations to the practical realities of high-frequency trading or data-driven decision-making.

    Behavioral & LeadershipHR ScreenBehavioralQuantitativeResearch
  • ImcHardSoftware Engineer
    When to use a dictionary vs an array?

    This question tests your understanding of the underlying trade-offs between contiguous memory structures (arrays) and hash-based key-value stores (dictionaries), focusing on performance, memory usage, and structural requirements.

    Software Engineering FundamentalsHR ScreenData StructuresMemory ManagementTime Complexity
  • InstacartMediumSoftware Engineer
    Describe your most complex end-to-end project

    Describe your most complex end-to-end project 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 & LeadershipHR Screen
  • InstacartMediumSoftware Engineer
    Design an inventory system

    This question evaluates a candidate's competency in designing inventory and distributed systems, covering stock tracking models, reservation and commit semantics, concurrency control, data modeling, API design, and real-time integrations.

    System DesignHR Screen
  • InstacartMediumData Scientist
    Diagnose and fix low conversion rigorously

    This question evaluates a Data Scientist's competency in analytics and experimentation, covering instrumentation validation, funnel and segmentation analysis, causal inference methods (holdouts/DiD), system reliability diagnostics, statistical power and sample-size estimation, and the ability to synthesize findings into executive-level impact statements. It is commonly asked to determine whether a candidate can distinguish measurement or product regressions from marketing-mix shifts and to demonstrate both conceptual understanding of causal inference and practical application of data querying, metric definition, and experiment design in the Analytics & Experimentation domain.

    Analytics & ExperimentationHR Screen
  • InstacartMediumSoftware Engineer
    Evaluate arithmetic expression using DFS

    This question evaluates a candidate's understanding of expression parsing and evaluation using depth-first traversal, covering competencies in recursive descent or stack-based DFS, operator precedence, unary operators, and 64-bit integer division semantics with truncation toward zero.

    Coding & AlgorithmsHR Screen
  • InstacartMediumData Scientist
    Explain handling very large datasets

    This question evaluates a candidate's competence in ingesting and processing very large datasets, covering storage formats and partitioning, memory and compute constraints, schema evolution, data quality checks, indexing strategies, tool selection in SQL/Python ecosystems, and code-level performance optimizations.

    Data Manipulation (SQL/Python)HR Screen
  • InstacartMediumData Scientist
    Justify Instacart fit and leaving your role

    This question evaluates a data scientist's ability to articulate company and product-market fit, quantify near-term impact, communicate transition logistics, and demonstrate self-awareness through managerial feedback and constraints.

    Behavioral & LeadershipHR Screen
  • InstacartHardData Scientist
    Lead a zero-to-one initiative effectively

    This question evaluates a data-oriented leader's ability to translate an ambiguous mandate into a measurable initiative by testing skills in problem definition, metric design, discovery and experimentation planning, stakeholder alignment, prioritization, and trade-off reasoning within a two-sided marketplace context.

    Behavioral & LeadershipHR Screen
  • InstacartMediumSoftware Engineer
    Optimize file reading and expression DFS

    This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Optimize file reading and expression DFS states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    Coding & AlgorithmsHR Screen
  • InstacartMediumSoftware Engineer
    Optimize file reads for password validation

    This question evaluates proficiency in on-disk file I/O, streaming algorithms, offline indexing for sublinear lookups, and system-level performance considerations for validating credentials in large files.

    Coding & AlgorithmsHR Screen
  • IntuitMediumData Scientist
    Compute churn and revenue churn in SQL

    This question evaluates a candidate's ability to compute subscription churn and revenue retention metrics from monthly snapshots, exercising SQL data-manipulation competencies such as handling missing or null MRR values, deduplicating snapshot loads, joining across months, and aggregating MRR changes.

    Data Manipulation (SQL/Python)HR Screen
  • IntuitMediumData Scientist
    Design an idempotent churn ETL pipeline

    This question evaluates a candidate's competence in designing robust ETL pipelines, covering idempotent processing, handling late-arriving streaming subscription events, SCD Type 2 slowly changing dimensions, incremental backfills, data quality checks, upsert/merge semantics, and metric versioning.

    Data Manipulation (SQL/Python)HR Screen
  • J.P. MorganMediumData Scientist
    Interpret Model Metrics, Regularization, and Resampling Fundamentals

    This problem tests your understanding of foundational machine learning metrics for imbalanced classification and the theoretical utility of regularization and resampling techniques.

    Statistics & MathHR ScreenStatisticsMachine LearningRegularization
  • Jane StreetMediumSoftware Engineer
    Calculate win chance in three-player dice game

    This question evaluates understanding of probability theory, conditional probability, and modelling of repeated stochastic events such as ties and rerolls, and is categorized under Statistics & Math.

    Statistics & MathHR Screen
  • LambdaHardSoftware Engineer
    Design a cloud AI inference platform

    This question evaluates competency in ML system design and operational engineering, covering model packaging and versioning, hardware selection (CPU vs GPU), autoscaling, request routing, multi-tenant isolation, SLO-driven observability, cost controls, and failure handling within a cloud inference platform.

    ML System DesignHR Screen
  • LambdaHardSoftware Engineer
    Design and explain infra, K8s, routing, and fleet

    This question evaluates system design and infrastructure engineering skills, including Infrastructure-as-Code and CI/CD for bare-metal and Kubernetes, secrets management, idempotency and drift control, Kubernetes control-plane and workload management, edge firmware and fleet OTA management, IP routing and troubleshooting, and the ability to demonstrate automation, networking, observability, and security through a homelab. It is commonly asked to assess operational design thinking, scalability, security, reliability, and troubleshooting across distributed systems, falls under the System Design and Platform Engineering domain, and tests both conceptual understanding of control-plane and networking principles and practical application of operational guardrails and rollout strategies.

    System DesignHR Screen
  • LinkedInMediumSoftware Engineer
    Implement map and render to DOM

    This question evaluates a candidate's skills in vanilla JavaScript utility implementation and DOM rendering, covering array and plain-object iteration semantics, higher-order functions, input validation, error handling, and safe text rendering for browser environments.

    Software Engineering FundamentalsHR Screen
  • LinkedInMediumSoftware Engineer
    Introduce yourself and discuss challenges

    This question evaluates communication, leadership, self-awareness, and the ability to concisely articulate technical impact, trade-offs, and measurable outcomes.

    Behavioral & LeadershipHR Screen
  • MetaMediumData Scientist
    Analyze ad targeting expectations and distributions

    This question evaluates a data scientist's competency in probabilistic modeling, expected-value decision-making, variance decomposition for mixture distributions, and Poisson/exponential arrival-process analysis within the Statistics & Math domain.

    Statistics & MathHR Screen
  • MetaHardData Scientist
    Choose and compute recommender evaluation metrics

    This question evaluates competency in offline recommender-system evaluation, propensity-weighted policy comparison, classification metric interpretation, probability calibration, model selection trade-offs, and handling data leakage and network interference.

    Machine LearningHR Screen
  • MetaEasySoftware Engineer
    Compute an Overnight Alarm Interval

    This problem tests the ability to calculate time intervals across date rollovers by converting 12-hour clock times into a continuous 24-hour linear timeline.

    Statistics & MathHR ScreenMathDate-TimeAlgorithms
  • MetaMediumProduct Analyst
    Describe an Analysis Where You Used AI Responsibly

    Prepare a credible story about using an AI-assisted tool in analysis. The exercise tests whether you can justify the tool, validate it independently, protect sensitive data, plan for failure, connect model quality to a product decision, and explain how you build AI fluency.

    Behavioral & LeadershipHR Screen
  • MetaEasySoftware Engineer
    Describe background and job motivations

    This question evaluates communication, self-awareness, motivation, and cultural-fit competencies within the Behavioral & Leadership domain for a Software Engineer role.

    Behavioral & LeadershipHR Screen
  • MetaHardSoftware Engineer
    Design a bank system with transfers

    This question evaluates system-design and transactional engineering skills for financial services, including API design, data modeling, correctness under holds and transfer expirations, idempotency, merge semantics, and complexity reasoning.

    System DesignHR Screen
  • MetaHardData Scientist
    Design a clustered A/B test with spillovers

    This question tests the ability to design a cluster-randomized experiment when interactions between users (network interference) violate the stable unit treatment value assumption (SUTVA).

    Analytics & ExperimentationHR ScreenCausal InferenceExperimental DesignStatistics
  • MetaMediumSoftware Engineer
    Solve array merge and tree flattening problems

    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 array merge and tree flattening problems states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    Coding & AlgorithmsHR Screen
  • MetaEasySoftware Engineer
    Solve four OA coding problems

    This set of coding tasks evaluates fundamental skills in array manipulation, graph traversal, greedy strategy, and sequence analysis.

    Coding & AlgorithmsHR ScreenArraysGreedyGraphs