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 301–330 of 781 results

  • FidelityMediumSoftware Engineer
    Write good tests and define integration tests

    Write good tests and define integration tests evaluates engineering fundamentals, trade-offs, examples, pitfalls, and operational implications in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    Software Engineering FundamentalsOnline Assessment
  • Five RingsHardData Scientist
    Solve coin probability and Bayesian inference problems

    This question evaluates probabilistic reasoning, stochastic-process intuition (pattern waiting times and runs), expected-value calculations, and Bayesian parameter estimation competency.

    Statistics & MathOnline Assessment
  • Goldman SachsEasyData Scientist
    Bound the Rank of BA Given Rank of AB

    Determine the set of possible values for the rank of the matrix product BA given that A and B are 4x4 real matrices and rank(AB) = 2. This question tests fundamental linear algebra inequalities involving matrix ranks and nullities.

    Statistics & MathOnline AssessmentLinear AlgebraMatrix TheoryRank Inequalities
  • Goldman SachsHardMachine Learning Engineer
    Complete decision tree and gradient descent functions

    This question evaluates implementation skills in supervised machine learning and numerical optimization, specifically computing Gini impurity and selecting optimal binary splits for a decision tree alongside deriving and applying a single-step gradient descent update for linear regression.

    Coding & AlgorithmsOnline Assessment
  • Goldman SachsEasyData Scientist
    Compute the Arc Length of a Curve

    Tests single-variable calculus fundamentals, specifically calculating the derivative, setting up the standard arc length integral, and evaluating it using substitution.

    Statistics & MathOnline Assessmentcalculusintegrationgeometry
  • Goldman SachsEasyData Scientist
    Count Palindromic Substrings

    This question tests your ability to identify palindromes within a string using expansion around centers or dynamic programming.

    Coding & AlgorithmsOnline AssessmentStringsTwo PointersDynamic Programming
  • Goldman SachsMediumSoftware Engineer
    Count segments and optimize 3-server assignment

    This two-part problem evaluates array-processing and counting competency for identifying fixed-length strictly increasing subarrays and combinatorial partitioning and optimization competency for assigning elements to three groups to maximize a minimal pairwise-difference metric, and is commonly asked to assess efficient algorithm design, correctness under constraints, and the ability to handle large inputs. Belonging to the Coding & Algorithms domain, it tests practical algorithmic application, data-structure-aware implementation and complexity analysis rather than purely theoretical understanding.

    Coding & AlgorithmsOnline Assessment
  • Goldman SachsHardMachine Learning Engineer
    Evaluate TPR/FPR, sigmoid, and activations

    This question evaluates competency in binary classification metrics (confusion matrices, TPR/FPR), basic neural network forward computation (sigmoid neuron z and output), and knowledge of activation function selection and pitfalls.

    Machine LearningOnline Assessment
  • Goldman SachsEasyData Scientist
    Expected Number of Runs in Coin Tosses

    Tests understanding of linearity of expectation and indicator random variables through counting consecutive runs in a sequence of coin tosses.

    Statistics & MathOnline Assessmentprobabilityexpected-valuecombinatorics
  • Goldman SachsEasyData Scientist
    Infer BA When AB Is the Identity

    This question tests the understanding of matrix invertibility, the properties of the identity matrix, and the fundamental differences between square and non-square matrix multiplication.

    Statistics & MathOnline AssessmentLinear AlgebraMatricesRank
  • Goldman SachsEasyData Scientist
    Integrate a Two-Sided Exponential Density

    This question tests the ability to integrate probability density functions (PDFs) over specified intervals, specifically handling the absolute value function in symmetric distributions.

    Statistics & MathOnline AssessmentCalculusProbabilityDistributions
  • Goldman SachsMediumProduct Manager
    Lottery Coupon Winners Calculation

    This question tests a candidate's ability to apply digit dynamic programming to efficiently count integers with specific digit-sum properties over large numeric ranges. It evaluates algorithmic thinking at the intersection of combinatorics and optimization, a category commonly assessed in technical interviews to measure comfort with non-obvious problem reductions and complexity trade-offs.

    Product / Decision MakingOnline Assessment
  • GoogleEasyData Scientist
    Answer Google Behavioral Questions

    A set of four common Google Data Scientist behavioral interview questions covering self-introduction and fit, diagnosing and solving a team problem, communicating a missed deadline to stakeholders, and handling a team event with reluctant participants. The solution uses a STAR/STAR-L framework and explains the competencies Google scores for: collaboration, ownership, communication, judgment, and inclusion.

    Behavioral & LeadershipOnline Assessment
  • GoogleEasyData Scientist
    Build next-word predictor with O(1) lookup

    This problem tests your ability to design a memory-efficient data structure for storing n-gram probabilities and performing fast lookups for the most likely next word.

    Coding & AlgorithmsOnline AssessmentHash MapData StructuresNLP
  • GoogleMediumSoftware Engineer
    Choose Your Workplace Style

    This item evaluates workplace-style competencies such as self-awareness, prioritization, consistency, communication, adaptability, and time-management in a software engineering context.

    Behavioral & LeadershipOnline Assessment
  • GoogleMediumSoftware Engineer
    Choose best/worst actions in workplace ethics scenarios

    This question evaluates workplace ethics, confidentiality handling, conflict-of-interest recognition, anti-harassment awareness, integrity, and escalation judgment for software engineers.

    Behavioral & LeadershipOnline Assessment
  • GoogleEasySoftware Engineer
    Compute max coins with 3-step token moves

    This question evaluates combinatorial optimization, state-space reasoning, and algorithmic design for constrained token movements on a linear board, and falls under the Coding & Algorithms domain.

    Coding & AlgorithmsOnline Assessment
  • GoogleMediumSoftware Engineer
    Consolidate On-Call Rotation Segments

    Consolidate overlapping on-call shift intervals into non-overlapping segments, each annotated with the sorted list of active engineers.

    Coding & AlgorithmsOnline Assessmentintervalsweep-linesorting
  • GoogleMediumSoftware Engineer
    Design a multi-timer using single underlying timer

    This question evaluates a candidate's ability to implement timer scheduling, resource multiplexing, and concurrency control using constrained system primitives, testing understanding of timers, event handling, data structures, and correctness under race conditions.

    Software Engineering FundamentalsOnline Assessment
  • GoogleEasySoftware Engineer
    Find largest digit-sharing subset

    This question evaluates a candidate's ability to reason about digit-based frequency analysis and efficient counting on arrays, testing competencies in combinatorics and algorithmic optimization for grouping elements by shared features.

    Coding & AlgorithmsOnline Assessment
  • GoogleEasySoftware Engineer
    Find largest group of two-digit numbers sharing digits

    This question evaluates a candidate's ability to model pairwise relationships and compute connected components in small graphs, testing skills in graph connectivity and grouping based on shared attributes in arrays of two-digit numbers.

    Coding & AlgorithmsOnline Assessment
  • GoogleMediumSoftware Engineer
    Implement Checksums and Feature Rollout Evaluation

    This question evaluates string processing, checksum computation with modular indexing, parsing of dependency data, and business-logic evaluation for feature rollouts, including conditional eligibility checks and dependency resolution.

    Coding & AlgorithmsOnline Assessment
  • GoogleMediumSoftware Engineer
    Maximize coins collected by tokens jumping +3

    Evaluates algorithmic reasoning about constrained discrete moves and optimization, focusing on state-space modeling, reachability under move constraints, and resource-maximization techniques.

    Coding & AlgorithmsOnline Assessment
  • GoogleHardSoftware Engineer
    Solve checksum and dependency debugging tasks

    Validate feature configuration strings using modular polynomial checksums and resolve valid deployment sequences using dependency graph analysis and cycle detection.

    Coding & AlgorithmsOnline Assessmentgraphtopological-sortstring-parsing
  • HBOHardData Scientist
    Define scalable train/validation for churn

    This question assesses the ability to design an end-to-end churn prediction pipeline, focusing on temporal integrity, handling class imbalance, and ensuring robust production deployment.

    Machine LearningOnline AssessmentChurnSystem DesignData Leakage
  • HBOHardData Scientist
    Design an A/B for rare cancellations

    This question evaluates a data scientist's competency in experimental design, rare-event power analysis, precise metric and guardrail definitions, variance-reduction covariate adjustment, sequential-testing decisions, monitoring/dashboard specification, and interpretation of heterogeneous treatment effects.

    Analytics & ExperimentationOnline Assessment
  • HackerRankMediumMachine Learning Engineer
    Build A Purchase-Intent Prediction Notebook

    Prepare for a machine learning take-home notebook that predicts purchase intent from session features and submits binary outcomes. The prompt focuses on data cleaning, missing values, categorical encoding, model pipelines, weighted F1, threshold tuning, and robust submissions.

    Machine LearningOnline Assessment
  • HackerRankMediumMachine Learning Engineer
    Count Good Subsequences With Equal Character Frequencies

    Practice a combinatorics coding problem that counts good subsequences where every selected character has the same frequency. The prompt targets frequency counting, combinations, modular arithmetic, and grouping subsequences by common selected count.

    Coding & AlgorithmsOnline Assessment
  • HackerRankMediumSoftware Engineer
    Debug React Sorting, Persistence, Routing, and Accessibility

    This problem tests your ability to identify and rectify common React anti-patterns, including state mutations, improper side-effect handling, and accessibility failures in a data-driven application.

    Software Engineering FundamentalsOnline AssessmentReactJavaScriptAccessibility
  • HeadlandsMediumData Scientist
    C++ Sliding-Window Mean of a Float Array With Inf, -Inf and NaN Handling

    Implement an O(n) sliding-window mean over a 32-bit float array containing IEEE-754 special values (+inf, -inf, NaN) without poisoning subsequent windows or suffering numerical drift.

    Software Engineering FundamentalsOnline Assessmentcppsliding-windowieee-754