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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 1951–1980 of 9403 results
- Capital OneEasyData AnalystAnalyze Mission Outcomes and Allocate Response Units
Analyze incident response records to calculate unit win rates, evaluate the impact of rest periods on success, and rank response units using tie-breakers.
Data Manipulation (SQL/Python)Online AssessmentPythonData ManipulationAnalytics - Capital OneMediumData ScientistAnalyze Subscription, Insurance, App, and Card Cases
This question evaluates product analytics competencies—unit-economics, cohort churn modeling, LTV/CAC and funnel math—requiring clear assumptions, metric definitions, governing formulas, and numeric break-even and conversion calculations.
Analytics & ExperimentationOnline Assessment - Capital OneMediumData ScientistAnalyze ad watch-time with Excel pivots
This question evaluates a data scientist's proficiency with Excel PivotTables, date and ISO-week handling, aggregation and ratio metrics (clicks per watch-minute), and deterministic tie-breaking logic for reproducible results.
Analytics & ExperimentationTechnical Screen - Capital OneMediumSoftware EngineerAnalyze and Debug Virtual-Card Payment Rules
Implement and debug a rule-validation engine for virtual card authorization that accurately parses currency strings into integer cents and evaluates spending boundaries and merchant restrictions.
Software Engineering FundamentalsOnsitePythonData ParsingBoundary Conditions - Capital OneMediumData ScientistAnalyze your favorite app and improve it
This question evaluates a data scientist's competencies in product analytics, monetization analysis, competitive positioning, metric specification (north-star and guardrails), and experimental design including power and validity considerations.
Analytics & ExperimentationOnsite - Capital OneMediumData EngineerAnswer conflict and ambiguity with STAR stories
This question evaluates a candidate's conflict-resolution, cross-functional communication, technical troubleshooting, ambiguity-management, and reflective learning competencies within a data engineering context.
Behavioral & LeadershipTechnical Screen - Capital OneMediumMachine Learning EngineerAnswer leadership scenarios with STAR
This question evaluates leadership, influence, problem-solving, prioritization, resilience, and the ability to deliver measurable results under constraints by eliciting STAR-format behavioral examples relevant to a Machine Learning Engineer role.
Behavioral & LeadershipOnsite - Capital OneMediumSoftware EngineerAnswer learning and challenge behavioral prompts
This question evaluates learning agility, problem-solving, influence, and leadership competencies by probing quick learning, process-challenging, and trade-off management in real work scenarios.
Behavioral & LeadershipTechnical Screen - Capital OneMediumSoftware EngineerAnswer motivation and teamwork questions
The question evaluates motivation, cultural fit, communication, teamwork, conflict-resolution, and the ability to describe concrete impact from collaborative work.
Behavioral & LeadershipTechnical Screen - Capital OneMediumSoftware EngineerApply commands to transform a matrix
This question evaluates array and matrix manipulation skills, specifically in-place row reversal, row swapping, and 90-degree rotation, and falls under the Coding & Algorithms domain with emphasis on practical implementation.
Coding & AlgorithmsOnline Assessment - Capital OneMediumData ScientistArticulate your most significant achievement
This question evaluates a Data Scientist's competency in demonstrating measurable impact, decision-making under constraints, experimental design, trade-off reasoning, and stakeholder management within the Behavioral & Leadership category of data science.
Behavioral & LeadershipTechnical Screen - Capital OneMediumData ScientistAssess Cultural Fit and Soft Skills in Interviews
This interview question evaluates behavioral evidence, ownership, communication, trade-offs, and measurable outcomes in a realistic interview setting. A strong answer for Assess Cultural Fit and Soft Skills in Interviews states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Behavioral & LeadershipOnsite - Capital OneMediumData ScientistAssess Customer Value with Varied Contract Terms and Costs
Evaluates subscription contract unit economics across free periods, service costs, marketing costs, churn penalties, and fixed overhead. Strong answers compute customer value, portfolio value, and break-even acquisitions.
Analytics & ExperimentationOnsite - Capital OneHardData ScientistAssess transition and profitability under fossil-fuel constraints
This question evaluates competency in data-driven energy transition analysis, quantitative modeling of generation mixes, economic pro-formas, and strategic decision-making under regulatory constraints.
Behavioral & LeadershipTechnical Screen - Capital OneMediumData ScientistAudit flight data quality from metadata
This question evaluates data quality auditing competencies, including validation of timestamps and timezones, detection of label leakage and inconsistent units, provenance and schema enforcement, and hands‑on use of SQL/Python for dataset inspection.
Data Manipulation (SQL/Python)Onsite - Capital OneMediumData ScientistAutomate Python Virtual Environment Setup on Linux Terminal
This question evaluates proficiency in shell scripting and Linux terminal automation for Python virtual-environment setup, focusing on environment management, automation, and reproducibility skills relevant to data science workflows.
Coding & AlgorithmsOnsite - Capital OneMediumSoftware EngineerBehavioral: Using AI Tools in Daily Engineering Work and to Improve Efficiency
A behavioral interview question for software engineers about AI tools: how you use them in day-to-day engineering work, and a specific example of how they improved your efficiency. It tests concrete examples, how AI output is verified, judgment about confidential code and data, and honest, measured results.
Behavioral & LeadershipTechnical Screen - Capital OneMediumSoftware EngineerBenefits of a Customer-Facing Chatbot for a Bank and Its Customers
A case-study opener asking what benefits a customer-facing chatbot would bring to a bank and to its customers. It tests whether you can tie each benefit to a concrete mechanism and metric, and weigh it against risks specific to banking such as wrong answers about money, authentication and privacy.
Product Design & StrategyOnsite - Capital OneMediumSoftware EngineerBlock-Building Operations: Check Whether a Free Segment Starts at a Position
Process operations on a number line that either place a block at a position or ask whether a segment of a given length starting at a position is free of blocks, and return the answers as a string of ones and zeros. It tests handling interleaved updates and range checks efficiently over large coordinates.
Coding & AlgorithmsOnline Assessment - Capital OneEasyData ScientistBuild House Price Model Responsibly
This problem tests your ability to design a robust, fair, and scalable machine learning pipeline for house price prediction, emphasizing data preprocessing, model selection, and ethical oversight.
Machine LearningOnsiteSupervised LearningRegressionFairness - Capital OneMediumSoftware EngineerBuild a Banking System with Activity Rankings
This problem tests your ability to design a system that maintains account state and dynamically updates an ordered leaderboard of account activity using efficient data structures.
Coding & AlgorithmsOnsiteHash MapBalanced BSTDesign - Capital OneHardData ScientistBuild a causal ML pipeline end-to-end
This question evaluates expertise in causal inference and policy learning, covering ATE/CATE estimation, heterogeneous treatment effect methods, off‑policy evaluation, overlap and sensitivity diagnostics, and operational deployment with fairness guardrails in the Analytics & Experimentation domain.
Analytics & ExperimentationOnsite - Capital OneMediumData ScientistBuild and evaluate donation propensity model
This question evaluates a data scientist's competency in profit-oriented predictive modeling, including conversion and donation-amount modeling, handling sparse and categorical features, calibration and uplift estimation, and offline policy evaluation under selection bias.
Machine LearningOnsite - Capital OneMediumSoftware EngineerBurner Card Numbers: Trade-offs, Hand Checks and a Buggy Validator
A three-part fintech case: weigh the trade-offs of disposable card numbers, check sample numbers by hand against format, Luhn and issuer-range rules, then find three bugs in a filter that rejects valid numbers and accepts invalid ones.
Software Engineering FundamentalsOnsitedebuggingluhnproduct-sense - Capital OneEasyData ScientistCalculate Annual Profit of Credit Card Portfolio
Evaluates annual profit calculation for a credit-card portfolio with monthly and annual revenue and cost components. Strong answers annualize figures, compute per-card profit, and scale to portfolio profit.
Statistics & MathHR Screen - Capital OneEasyData ScientistCalculate Incremental Customers for Marketing Spend Justification
Evaluates incremental customer calculations for partnership marketing spend justification. Strong answers derive break-even customers for fixed spend and required volume for variable-cost campaigns against a profit target.
Statistics & MathHR Screen - Capital OneMediumData ScientistCalculate Longest Transaction Streak for Each User
This question evaluates proficiency in data manipulation and time-series sequence analysis, specifically measuring the longest run of consecutive successful transactions per user from transactional logs.
Data Manipulation (SQL/Python)Technical Screen - Capital OneMediumData ScientistCalculate Profit and Analyze Vegan Burger Market Trends
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 Calculate Profit and Analyze Vegan Burger Market Trends states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Analytics & ExperimentationTechnical Screen - Capital OneEasyData ScientistCalculate Profitability and Break-Even for Lyft Partnership Campaign
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 Calculate Profitability and Break-Even for Lyft Partnership Campaign states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Analytics & ExperimentationHR Screen - Capital OneMediumData ScientistCalculate break-even new customers for a 30% Rent-a-Home discount
A Capital One data-scientist technical screen on break-even and unit economics for a 30%-off Rent-a-Home promotion. You set up and solve the break-even equation for incremental new customers, size it against the 2M cardholder base, then re-solve under spend-uplift assumptions and explain why the required count nearly doubles.
Statistics & MathTechnical Screen
Capital One