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Interview questions
Explore algorithm tutorials, coding and system design questions, interview experiences, and computer science study guides.
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Interview questions · Pinterest
Settle debts with minimal transactions
Pinterest software-engineer onsite coding question: given a list of debts as (debtor, creditor, amount) triples, return settlement transfers that clear every net balance using the minimum number of transactions. It tests reducing to net balances, recognizing the problem is NP-hard, backtracking with pruning to find the optimum for small N, and a heap-based greedy heuristic plus correctness and time/space complexity analysis for large, skewed debt graphs.
Interview questions · Databricks
Share background, conflicts, and proud project details
This interview question evaluates behavioral evidence, ownership, communication, trade-offs, and measurable outcomes in a realistic interview setting. A strong answer for Share background, conflicts, and proud project details states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Interview questions · Figma
Share behavioral stories
This interview question evaluates behavioral evidence, ownership, communication, trade-offs, and measurable outcomes in a realistic interview setting. A strong answer for Share behavioral stories states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Interview questions · Meta
Share different perspective from leadership feedback
This question evaluates a software engineer's ability to receive and integrate leadership feedback, measuring competencies such as adaptability, self-awareness, communication, and accountability.
Interview questions · Amazon
Share examples of impact and simplicity
This interview question evaluates behavioral evidence, ownership, communication, trade-offs, and measurable outcomes in a realistic interview setting. A strong answer for Share examples of impact and simplicity states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Interview questions · Netflix
Show Behavioral Fit and Experience
Show Behavioral Fit and Experience 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.
Interview questions · Coinbase
Show culture add at Coinbase
This question evaluates behavioral and leadership competencies for a Data Scientist role, focusing on cultural fit, clear communication, trade-off decision-making between speed, compliance/security and user experience, stakeholder management, hiring judgment, and measurable execution impact.
Interview questions · Capital One
Show help, mistake recovery, and achievement
This question evaluates collaboration under pressure, rapid incident detection and recovery, metrics-driven decision-making, and the ability to influence without formal authority, emphasizing technical judgment, stakeholder communication, and leadership competence in a Data Scientist context within the Behavioral & Leadership domain.
Interview questions · TikTok
Show ownership in ambiguous creator-growth work
This question evaluates product-oriented data science competencies including end-to-end ownership, problem framing and success-metric definition, trade-off prioritization, cross-functional influence, experimentation and uncertainty management, geo-aware adaptation, and long-term system-health safeguards.
Interview questions · Netflix
Show role fit using past ad experience
This question evaluates a candidate's ability to demonstrate role fit by mapping past ads engineering projects to job requirements and communicating measurable impact, assessing competencies such as ownership, cross-functional collaboration, incident debugging, and prioritization.
Interview questions · Bank of America
Showcase initiative and collaboration examples
This prompt evaluates initiative, ownership, quantitative rigor, complex problem-solving, and relationship-building within a data scientist role. Commonly asked to gauge leadership, cross-functional impact, and measurable technical outcomes, it is categorized as Behavioral & Leadership in the data science domain and emphasizes practical application of analytical methods alongside conceptual reasoning about trade-offs and collaboration.
Interview questions · Moloco
Simulate bubble elimination and maximize common prefix
This multi-task question evaluates simulation and array manipulation skills for the grid elimination task and scalable string-processing and prefix-search techniques for the longest common prefix task, testing competency in state updates, pattern detection, and efficient data-structure use.
Interview questions · Uber
Simulate fixed-shape tiling on a grid
This question evaluates a candidate's ability to implement grid-based simulation and pattern-matching algorithms, including handling fixed-shape placements, internal holes, bounds checking, collision detection, and explicit scanning/tie-breaking rules.
Interview questions
Simulate via inverse transform and Gibbs
This question evaluates understanding of random variate generation and Markov chain Monte Carlo techniques, specifically inverse-transform sampling for the Logistic(μ,s) distribution and Gibbs sampling for a bivariate joint density, testing competency in probability theory, distribution properties, and statistical computing within the Statistics & Math domain. It is commonly asked to assess the ability to derive inverse CDFs and full conditional distributions, verify sample correctness with goodness-of-fit and convergence diagnostics, and reason about sample size, burn-in, and thinning, reflecting a mix of conceptual understanding and practical application.
Interview questions · Uber
Simulate views on an n-ary tree
This question evaluates proficiency in tree traversal and algorithm design for ordered n-ary trees, focusing on identifying visible boundary nodes given child ordering and reasoning about time and space complexity.
Interview questions · Meta
Size opportunity for new product line
This question evaluates a data scientist's skills in financial opportunity sizing, sensitivity analysis, and experimental design by requiring quantitative modeling of impacted users, incremental orders, revenue, and gross profit for a proposed product line.
Interview questions · Pinterest
Solve a 9x9 Sudoku puzzle
This question evaluates algorithmic problem-solving skills focused on constraint satisfaction, state-space search, and implementation correctness for combinatorial puzzles.
Interview questions · Instacart
Solve a challenge using data
This behavioral interview question assesses a Data Scientist's ability to demonstrate end-to-end analytical rigor, from hypothesis formation and experimental design to stakeholder communication and quantified business impact. It tests causal reasoning, metric design, and cross-functional judgment — core competencies evaluated in data science roles across product and technology organizations.
Interview questions · Snapchat
Solve a two-jug measuring problem
This question evaluates algorithm design, state-space modeling, graph-search techniques (BFS/DFS) and number-theoretic reasoning (gcd), along with handling edge cases and analyzing time and space complexity in the Coding & Algorithms domain.
Interview questions · Meta
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.
Interview questions · Instacart
Solve bank, password, expression algorithm tasks
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 bank, password, expression algorithm tasks states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Interview questions · Microsoft
Solve binary-tree reverse printing and LPS
This question evaluates proficiency with tree data structures and level-order traversal semantics for reverse level printing, as well as string algorithmic reasoning and dynamic programming concepts for computing the longest palindromic subsequence, categorized under Coding & Algorithms.
Interview questions · Box
Solve classic troubleshooting & algorithm tasks
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 classic troubleshooting & algorithm tasks states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Interview questions · Meta
Solve common array/string/linked-list tasks
This set of tasks evaluates algorithmic problem-solving and data-structure manipulation across arrays, strings, and linked lists, including probabilistic sampling, in-place space optimization, expression parsing, efficient search, and substring/sequence analysis while requiring explicit time and space complexity reasoning.