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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.
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- 546
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Showing 991–1020 of 4616 results
- 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 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 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 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 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 OneEasyData ScientistCalculate first-year profit margin
This question evaluates a data scientist's quantitative reasoning about unit economics and financial metrics, including understanding fixed versus variable costs and computing profit margin as a percentage.
Statistics & MathTechnical Screen - Capital OneEasyData ScientistCalculate profit and break-even across pricing models
This question evaluates understanding of unit economics, break-even analysis, and pricing-model effects on profitability by requiring computation of revenue, variable and fixed costs, and profit under per-GB and two-tier pricing scenarios.
Statistics & MathTechnical Screen - Capital OneMediumProduct ManagerCapital One Credit Card: Acquisition & Promotion Strategy
Practice a Capital One credit card acquisition and promotion strategy case for a mid-tier rewards card. The solution covers target segments, channel strategy, funnel goals, promotion trade-offs, sign-up bonus ROI, risk guardrails, payback logic, and metrics for profitable account growth.
Product / Decision MakingTechnical Screen - Capital OneMediumSoftware EngineerCard Issuer Backend: Fast Purchase Approvals and a Secure PII Vault
Design the issuer-side platform that approves or declines card purchases in tens of milliseconds, settles them later, and stores cardholder identity data so a breach of any one service exposes as little as possible.
System DesignTechnical Screensystem-designpaymentslatency - Capital OneHardData ScientistChallenge and validate assumptions
This question evaluates a data scientist's competency in identifying fragile business assumptions, conducting sensitivity analysis, and designing experiments and observational studies to validate parameters related to demand, price elasticity, cannibalization, supply constraints, labor learning curves, regional heterogeneity, and promotional decay.
Analytics & ExperimentationTechnical Screen - Capital OneMediumData ScientistCompare Logistic Regression and Random Forest in Python
Design, evaluate, and contrast a Logistic Regression baseline and a Random Forest model on an imbalanced credit default prediction dataset in Python. Walk through pipeline design, validation strategy, probability calibration, decision thresholding, and production trade-offs.
Machine LearningTechnical ScreenClassificationModel EvaluationPipelines - Capital OneMediumData AnalystCompare Two-Year Economics for Renewing or Replacing a Show
Calculate two-year show profits, derive the success-probability break-even point, and evaluate renewal and profit-improvement choices.
Analytics & ExperimentationTechnical Screen - Capital OneEasyData ScientistCompare average profit across mix scenarios
This question evaluates understanding of expected value, weighted averages, and profit-margin analysis within the Statistics & Math domain for a Data Scientist role. It is commonly asked to probe quantitative reasoning about pricing and cost trade-offs, and it tests practical application of arithmetic and scenario-based profit modeling rather than abstract theoretical concepts.
Statistics & MathTechnical Screen - Capital OneEasyData ScientistCompare average unit profit under mix shift
This question tests the candidate's ability to calculate weighted averages and understand how changes in sales volume distribution (mix shift) affect the overall average profit per unit.
Statistics & MathTechnical ScreenStatisticsWeighted AverageUnit Economics - Capital OneEasyData ScientistCompute Groupon unit economics and break-even
A Capital One data science technical screen case on restaurant unit economics with a Groupon-style voucher. You compute baseline daily profit from a 20-table day, derive the break-even check for a voucher table under a $30-for-$15 offer with a 40% commission, profit a mixed 25-table day, and decompose the profit change into traffic, check size and voucher cost. Full worked arithmetic, a sensitivity solve, and the incrementality follow-ups an interviewer expects.
Statistics & MathTechnical Screen - Capital OneEasyData ScientistCompute current annual profit
This question evaluates numerical proficiency in financial arithmetic, unit-aware quantitative reasoning, and per-customer business-metric computation within a loyalty program context.
Statistics & MathTechnical Screen - Capital OneEasyData ScientistCompute incremental profit, breakeven, and revenue sensitivity
A Capital One data scientist technical-screen case on cost accounting and profitability modeling. Candidates compute the Year-1 incremental profit of a new vegan burger line, decompose it into fixed versus variable components, derive breakeven volume, and run a ±10% sensitivity analysis.
Statistics & MathTechnical Screen - Capital OneMediumData ScientistCompute optimal stopping in a die-rolling game
This question evaluates a candidate's grasp of optimal stopping theory, expected value computation, and finite-horizon decision-making under uncertainty, including recognition of threshold-based policies and backward-induction reasoning relevant to data scientist roles.
Statistics & MathTechnical Screen - Capital OneMediumData ScientistCompute partnership profit and break-even population
This question evaluates competency in analytics and experiment-driven financial modeling, covering unit economics, cannibalization versus true lift, break-even and sensitivity analysis, and interpretation of segment-level impacts on partnership profitability.
Analytics & ExperimentationTechnical Screen - Capital OneMediumData ScientistCompute profit and break-even for memberships
This problem tests your ability to model unit economics for a subscription-based loyalty program and perform sensitivity analysis to determine the break-even point for a business intervention.
Statistics & MathTechnical ScreenEconomicsLinear ModelingBreak-even Analysis - Capital OneMediumData ScientistCompute required output to recover 10% investment
This question evaluates a candidate's ability to perform cost-volume-profit analysis and quantitative financial modeling, assessing skills in algebraic formulation of profit equations, capacity constraint evaluation, and derivation of generalized feasibility formulas.
Statistics & MathTechnical Screen - Capital OneMediumData ScientistCompute unit economics and insurance break-even
This question evaluates a candidate's proficiency in unit economics, insurance break-even analysis, expected-value modeling, churn effects, pricing versus demand trade-offs, and basic statistical inference including MLE and confidence intervals.
Statistics & MathTechnical Screen - Capital OneMediumSoftware EngineerCount Numbers With Odd Zeros
This question evaluates proficiency in numeric digit analysis and parity-based counting, testing the competency to reason about decimal representations of integers within the Coding & Algorithms domain at a practical application level. It is commonly asked to assess basic algorithmic thinking, efficient iteration and counting skills, and careful handling of edge cases in technical interviews.
Coding & AlgorithmsTechnical Screen - Capital OneMediumData ScientistCritique a product interface and propose fixes
This question evaluates a candidate's product-thinking and usability analysis skills, specifically application of heuristics and accessibility standards alongside abilities in redesign proposal, success-metrics definition, and experiment/telemetry planning.
Behavioral & LeadershipTechnical Screen - Capital OneMediumData ScientistCritique and Test Python Preprocessing Utilities Effectively
This question evaluates a candidate's ability to review and critique Python preprocessing utilities, covering competencies in software design patterns (fit/transform separation), coding style and import hygiene, and unit-test specification for data-science pipelines.
Coding & AlgorithmsTechnical Screen - Capital OneMediumData ScientistDecide Which Show to Renew
This problem tests the ability to calculate expected value and ROI for a business decision under uncertainty, requiring the candidate to incorporate subscriber churn risk and lifetime value metrics.
Analytics & ExperimentationTechnical ScreenExpected ValueROIChurn Analysis - Capital OneMediumData ScientistDecide and test Groupon program incrementality
This question evaluates experimental design, causal inference, uplift and profitability modeling, operational risk assessment, and KPI-driven decision rules within the Analytics & Experimentation domain for data scientists, testing both conceptual understanding and practical application of A/B testing, sample-size considerations, and guardrail metrics. It is commonly asked to determine whether a candidate can translate business constraints into a rigorous experiment and profit-oriented analysis, balancing incremental impact estimation, cannibalization concerns, and operational trade-offs to support go/no-go decisions.
Analytics & ExperimentationTechnical Screen - Capital OneHardData ScientistDecide on vegan-burger R&D investment
This question evaluates quantitative business-case construction, including market sizing (TAM/SAM/SOM), unit economics and financial modeling, risk assessment and option valuation, plus experimental-design skills within the Analytics & Experimentation domain for a Data Scientist role.
Analytics & ExperimentationTechnical Screen - Capital OneMediumData ScientistDecide whether to invest in R&D
This question evaluates a data scientist's competency in data-driven decision-making, financial modeling, product strategy, and cross-functional leadership by requiring synthesis of customer insight, NPV and cost analysis, cannibalization effects, operational risks, brand positioning, and a staged rollout plan.
Behavioral & LeadershipTechnical Screen
Capital One