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 1891–1920 of 4616 results

  • GrammarlyMediumSoftware Engineer
    Reverse a Singly Linked List

    This problem tests your understanding of pointer manipulation and iterative/recursive techniques for modifying linked structures in-place.

    Coding & AlgorithmsTechnical ScreenLinked ListIn-placePointer Manipulation
  • Grayswan AiEasySoftware Engineer
    Implement a debounced function (with leading option)

    This problem tests your understanding of higher-order functions, closure scope, and asynchronous execution control by requiring the implementation of a flexible debounce utility.

    Coding & AlgorithmsTechnical ScreenJavaScriptClosuresAsynchronous
  • GrindrMediumData Scientist
    How would you evaluate causal lift and a paywall change?

    A two-part Grindr Data Scientist technical screen on analytics and experimentation. Part 1 designs an advertiser-level causal study for a new ad-optimization product when the eligible advertiser pool is too small, covering MDE/power, CUPED, matched-pair and panel designs, interference, and heterogeneous effects. Part 2 evaluates lowering a free-user paywall from 100 to 80 profiles, balancing short-term conversion against long-term LTV, retention, ad revenue, and one-sided-triggering selection bias.

    Analytics & ExperimentationTechnical Screen
  • GsaMediumData Scientist
    Critique a CNN-Based Bridge Safety Proposal

    This question tests the ability to identify flaws in a computer vision project, focusing on data validity, label sparsity, adversarial robustness, and the practical limitations of predictive modeling in structural engineering.

    Machine LearningTechnical ScreenComputer VisionAdversarial MLData Ethics
  • GsaHardData Scientist
    Optimize Matrix-Chain Multiplication

    This problem tests your ability to solve a classic dynamic programming challenge, focusing on finding the optimal order of matrix multiplications to minimize the total number of scalar operations.

    Coding & AlgorithmsTechnical ScreenDynamic ProgrammingAlgorithmsOptimization
  • GsaHardData Scientist
    Predict Stock Returns from Sentiment and Market Data

    This problem tests the ability to design an end-to-end predictive pipeline for stock returns, focusing on time-series integrity, feature engineering, and robust evaluation metrics.

    Machine LearningTechnical ScreenFinancial ModelingTime SeriesData Leakage
  • GustoMediumData Scientist
    Build Churn Prediction and Survival Models

    This problem tests the ability to design an end-to-end churn prediction pipeline, specifically focusing on the distinction between binary classification and survival analysis in the context of customer retention.

    Machine LearningTechnical ScreenChurn PredictionSurvival AnalysisFeature Engineering
  • GustoMediumData Scientist
    Calculate Net Pay Change for Q1 2023 Decreases

    This question evaluates a candidate's data-manipulation competency in SQL and Python, focusing on computing net pay, aggregating over a calendar quarter, and measuring percentage change between recent pay periods.

    Data Manipulation (SQL/Python)Technical Screen
  • GustoMediumData Scientist
    Compute Parking Clustering Probability and P-Value

    This question tests your ability to calculate exact combinatorial probabilities under a null hypothesis and define a p-value for a spatial clustering test.

    Statistics & MathTechnical ScreenProbabilityCombinatoricsHypothesis Testing
  • GustoEasyData Scientist
    Compute p-values for 2 variants vs control

    This question evaluates a candidate's competence in statistical hypothesis testing and experiment analysis, focusing on A/B/n comparison of conversion rates, p-value computation, confidence interval estimation for lift, multiple-testing considerations, and interpretation of results.

    Analytics & ExperimentationTechnical Screen
  • GustoMediumData Scientist
    Describe Your Analytical Experience and Cross-Functional Collaboration.

    This interview question evaluates behavioral evidence, ownership, communication, trade-offs, and measurable outcomes in a realistic interview setting. A strong answer for Describe Your Analytical Experience and Cross-Functional Collaboration. states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    Behavioral & LeadershipTechnical Screen
  • GustoMediumSoftware Engineer
    Design restaurant shift scheduling

    This problem tests your ability to design a scalable scheduling system, specifically focusing on data modeling for temporal availability, handling conflicting shift assignments, and API design for concurrent updates.

    System DesignTechnical ScreenConcurrencyData ModelingScalability
  • GustoMediumSoftware Engineer
    Fairly Distribute Money With Limits

    This problem tests your ability to implement a greedy allocation algorithm while respecting individual upper bounds and handling iterative redistribution of remaining resources.

    Coding & AlgorithmsTechnical ScreenGreedyBinary SearchSorting
  • GustoMediumData Scientist
    How do you test two variants vs control?

    This question evaluates proficiency in A/B/n experimentation, hypothesis testing for binomial proportions, multiple-comparison correction methods, confidence interval estimation for conversion uplift, and experiment-related decision-making in the Analytics & Experimentation domain at an applied/intermediate statistical-analysis level.

    Analytics & ExperimentationTechnical Screen
  • GustoMediumData Scientist
    Identify Growth Opportunities for New Payroll Feature Launch

    This interview question evaluates metric design, causal reasoning, experiment setup, diagnostics, SQL/statistical checks, and recommendations in a realistic interview setting. A strong answer for Identify Growth Opportunities for New Payroll Feature Launch states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    Analytics & ExperimentationTechnical Screen
  • GustoMediumSoftware Engineer
    Implement a timestamped map

    This problem tests your ability to design a time-indexed key-value store that supports efficient lookups of historical values using binary search.

    Coding & AlgorithmsTechnical ScreenHash MapBinary SearchData Structures
  • GustoMediumData Scientist
    Investigate Causes of Increased Payroll Processing Time

    This interview question evaluates metric design, causal reasoning, experiment setup, diagnostics, SQL/statistical checks, and recommendations in a realistic interview setting. A strong answer for Investigate Causes of Increased Payroll Processing Time states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    Analytics & ExperimentationTechnical Screen
  • HackerRankMediumSoftware Engineer
    Design a URL Shortener

    This question assesses the ability to design a URL shortening service (like Bitly) focusing on scalability, distributed ID generation, and efficient data retrieval.

    System DesignTechnical ScreenScalabilityDatabaseCaching
  • HackerRankMediumSoftware Engineer
    Find Final Ball Holder

    This problem tests your ability to optimize repeated state transitions by identifying cycles in a functional graph or using modular arithmetic to jump through large steps.

    Coding & AlgorithmsTechnical ScreenMathModulo ArithmeticSimulation
  • HadrianHardSoftware Engineer
    Work Order Lead Time: Critical Path Through an Operations DAG to Shipping

    A manufacturing work order is modeled as a directed acyclic graph of operations with durations in days, and every path ends at one shipping node. Compute the total lead time as the critical path length from any starting operation to shipping. It tests graph modeling, dependency ordering and longest-path reasoning.

    Coding & AlgorithmsTechnical Screen
  • HarveyMediumFrontend Engineer
    Build a Virtualized React Spreadsheet with Cell Formulas

    Design and implement a virtualized React spreadsheet component supporting editable cells, formula evaluation with string concatenation, cycle detection, and targeted re-rendering.

    Software Engineering FundamentalsTechnical ScreenReactVirtualizationGraph Algorithms
  • HarveyMediumSoftware Engineer
    Describe Leading a Technical Project

    This question evaluates leadership, ownership, collaboration, technical judgment, and project management skills within the Behavioral & Leadership domain of software engineering.

    Behavioral & LeadershipTechnical Screen
  • HarveyMediumSoftware Engineer
    Design a Cloud File Storage Service

    This question evaluates competency in designing large-scale distributed file storage and collaboration systems, covering storage and metadata modeling, API design, synchronization and consistency models, resumable large-file handling, versioning, access control, scalability, availability, durability, and security.

    System DesignTechnical Screen
  • HarveyMediumSoftware Engineer
    Design a constrained in-memory file system

    This question evaluates design and implementation skills for hierarchical in-memory data structures, string parsing and file-name collision handling under constraints, and the ability to reason about time and space complexity.

    Coding & AlgorithmsTechnical Screen
  • HarveyHardSoftware Engineer
    Design a production file storage service

    This question evaluates a candidate's competency in distributed systems and storage architecture, covering metadata schema design, concurrency control for atomic per-directory limits and renaming, transaction boundaries and idempotency, storage models for file bytes, large-file handling, consistency and failure modes, scalability and partitioning, observability, lifecycle management, and security. It is in the System Design domain and is commonly asked because it reveals how a candidate reasons about architectural trade-offs and practical implementation concerns; it tests both high-level conceptual design and hands-on practical application.

    System DesignTechnical Screen
  • HarveyHardSoftware Engineer
    Design an In-Memory Spreadsheet Engine

    Design an in-memory spreadsheet engine that supports cell updates, formula evaluations, cycle detection, and O(1) value lookups via proactive cache propagation.

    Coding & AlgorithmsTechnical ScreenGraphTopological SortSystem Design
  • HarveyMediumSoftware Engineer
    Design an in-memory file system with limits

    This question evaluates the ability to design and implement hierarchical in-memory data structures, manage capacity constraints and OS-style duplicate naming, and reason about edge cases and time/space complexity.

    Coding & AlgorithmsTechnical Screen
  • HarveyHardSoftware Engineer
    Determine identical files ignoring metadata

    A Harvey AI system design screen on determining whether two files are byte-identical while ignoring metadata, then scaling to deduplication. It covers hashing algorithm choice (SHA-256/BLAKE3 vs MD5/xxHash), multi-stage verification, collision and false-positive mitigation, streaming and parallel hashing, content-defined chunking, and persistent hash-index/service design.

    System DesignTechnical Screen
  • HarveyMediumSoftware Engineer
    Eager Spreadsheet Formulas with Constant-Time Reads

    Implement eager spreadsheet formulas with constant-time cached reads, transitive dependency updates, cycle rejection, and atomic definition replacement.

    Coding & AlgorithmsTechnical Screen
  • HarveyMediumSoftware Engineer
    Find Duplicate Files Safely at Scale

    Design and implement a robust file duplicate finder that handles filesystem cycles, minimizes disk I/O using multi-stage filtering, and avoids loading entire large files into memory.

    Software Engineering FundamentalsTechnical ScreenFile SystemsI/O OptimizationHashing