Data Scientist Interview Questions

Showing 841–870 of 1076 results

• SnapchatMedium·Data Scientist
  Analyze OLS After Duplicating Every Observation

  This question tests your understanding of OLS coefficient estimation and standard error calculations under the scenario of duplicate data observations.

  Statistics & MathTechnical ScreenOLSLinear RegressionStatistics
• SnapchatMedium·Data Scientist
  Calculate Average Camera Switches per Session

  Tests the ability to write a PostgreSQL query using window functions (LAG) to compute the average number of specific state transitions per session while accounting for zero-transition sessions and avoiding integer division.

  Data Manipulation (SQL/Python)Technical ScreenSQLPostgreSQLWindow Functions
• SnapchatMedium·Data Scientist
  Compute same-day acceptance metrics last week

  This question evaluates proficiency in time-based data manipulation, SQL JOINs and aggregations, handling NULLs and missing reference rows, and computing acceptance and percentage metrics with careful UTC date boundary treatment.

  Data Manipulation (SQL/Python)Technical Screen
• SnapchatMedium·Data Scientist
  Count Users Whose First Daily Event Is App Launch

  Write a PostgreSQL query to identify each user's first event per calendar day and aggregate the distinct user count by operating system and device when that first event is an app launch. Tests window functions, tie-breaking logic, and multi-dimensional grouping.

  Data Manipulation (SQL/Python)Technical ScreenSQLPostgreSQLWindow Functions
• SnapchatHard·Data Scientist
  Design an experiment for spam filtering impact

  This question evaluates experimental design and causal inference skills for measuring the effect of a stricter spam filter on same-day friend-request acceptance, covering hypothesis specification, interference and randomization choices, metric definition and windows, power calculation, and handling incomplete labels.

  Analytics & ExperimentationTechnical Screen
• SnapchatMedium·Data Scientist
  Diagnose Violations of Linear Regression Assumptions

  Tests a candidate's systematic understanding of ordinary least squares (OLS) regression assumptions, distinguishing how specific violations compromise unbiased point estimation, standard error inference, and predictive accuracy.

  Statistics & MathTechnical ScreenStatisticsLinear RegressionEconometrics
• SnowflakeMedium·Data Scientist
  Contrast FCF vs NI; choose one statement

  This question evaluates financial statement analysis skills—specifically reconciling net income to free cash flow, identifying accounting and working-capital red flags, and selecting which single statement best informs credit risk, profitability trends, and cash runway, thereby testing valuation, solvency, and financial-modeling competency in the Statistics & Math domain. It is commonly asked because interviewers probe both conceptual understanding and practical application of accrual versus cash accounting, the effects of non‑cash charges, capex and working‑capital movements on valuation, and awareness of which metrics (for example FCF margin, interest coverage, and current ratio) become unreliable or unobtainable when only one statement is available.

  Statistics & MathTechnical Screen
• SnowflakeMedium·Data Scientist
  Describe navigating ambiguous, repetitive questioning

  This question evaluates a Data Scientist's skills in stakeholder communication, ambiguity management, diagnostic reasoning to identify misaligned goals or definitions, adaptive framing between technical and plain-language explanations, trade-off analysis under time pressure, and delivering measurable outcomes.

  Behavioral & LeadershipTechnical Screen
• SnowflakeHard·Data Scientist
  Design an A/B test for ML model launch

  This question evaluates a data scientist's competence in experimental design, statistical power analysis, sequential monitoring, covariate adjustment (e.g., CUPED), and practical operational concerns like guardrails, interference, and ramping for ML model launches.

  Analytics & ExperimentationTechnical Screen
• SnowflakeHard·Data Scientist
  Design and validate a cost-sensitive classifier

  This question evaluates competence in cost-sensitive binary classification, handling delayed and imbalanced labels, calibration and decision-threshold selection, distributional-drift detection, monitoring, and low-latency deployment within the Machine Learning / Data Science domain.

  Machine LearningTechnical Screen
• SnowflakeHard·Data Scientist
  Implement DFS with cycle detection and topo order

  This question evaluates mastery of graph algorithms—specifically depth-first search (both recursive and iterative), directed cycle detection, topological ordering, and discovery/finish timestamping—and falls under the Coding & Algorithms domain.

  Coding & AlgorithmsTechnical Screen
• SnowflakeMedium·Data Scientist
  Lead innovation and automate a critical process

  This question evaluates leadership and technical program management competencies for a Data Scientist, including end-to-end innovation, cross-functional stakeholder alignment, risk identification and mitigation, trade-off rationale, measurable impact assessment, and process automation architecture and maintainability.

  Behavioral & LeadershipTechnical Screen
• SnowflakeMedium·Data Scientist
  Query seven-day conversion with windows and dedupe

  This question evaluates proficiency in time-windowed aggregations, event deduplication, and window-function–based user-level analytics across SQL and Pandas workflows.

  Data Manipulation (SQL/Python)Technical Screen
• SoFiMedium·Data Scientist
  Align with PM on ranking goals

  This question evaluates stakeholder alignment, risk management, product-ranking trade-offs, regulatory and compliance awareness, metric definition, and communication and negotiation skills relevant to delivering an MVP while planning a future ML iteration.

  Behavioral & LeadershipTechnical Screen
• SoFiHard·Data Scientist
  Plan and validate ranking experiment

  This question evaluates skills in experimental design and analytics, covering offline counterfactual replay, interleaving and A/B testing, sample-size and power computation, sequential testing and alpha spending, guardrail monitoring and ramp policies, proxy metrics and covariate adjustment, heterogeneous treatment effect analysis, and governance concerns such as p-hacking and Simpson’s paradox within the Analytics & Experimentation domain for Data Scientist roles. It is commonly asked to probe proficiency in rigorously validating ranking changes while balancing statistical error, operational risk and bias mitigation, and it emphasizes practical application of applied statistical concepts and experiment governance rather than purely theoretical understanding.

  Analytics & ExperimentationTechnical Screen
• SquarepointHard·Data Scientist
  Analyze expectations, correlations, and investment strategies

  This problem tests your understanding of stochastic processes in finance, the linear algebraic requirements for covariance matrices, and optimal decision-making under uncertainty.

  Machine LearningTechnical ScreenProbabilityLinear AlgebraStochastic Calculus
• SquarepointMedium·Data Scientist
  Compare Bonds, Common Equity, and Dividend Payments

  Compare debt and common equity claims, cash flows, risks, and why company profits do not guarantee common-share dividends.

  Statistics & MathTechnical Screen
• SquarepointMedium·Data Scientist
  Compare Winning Chances in a Card Game That Replays Ties

  Use symmetry and tied-round replay to compare two players drawing cards without replacement and derive the game's eventual winning probabilities.

  Statistics & MathTechnical Screen
• SquarepointMedium·Data Scientist
  Compute drawdown, profit, and coin change

  This question evaluates a candidate's ability to compute financial time-series metrics and apply algorithmic techniques such as array processing and optimization/dynamic programming to identify maximum drawdown and its indices.

  Coding & AlgorithmsTechnical Screen
• SquarepointMedium·Data Scientist
  Count Index Triplets With an Even Product Modulo a Given Number

  From a Squarepoint technical screen: count the triplets of distinct positions in an integer array whose three values have an even product, and return the count modulo a given number. It tests efficient counting on large inputs, parity with zero and negative values, and remembering to apply the required modulo.

  Coding & AlgorithmsTechnical Screen
• SquarepointMedium·Data Scientist
  Count Ways to Reach Step n With a Given Set of Step Sizes

  From a Squarepoint technical screen: count the ordered sequences of moves that climb exactly n stairs when every move uses a step size from a given set. It tests careful counting of ordered choices, targets that cannot be reached, and the interviewer's follow-up about reducing the extra space the solution uses.

  Coding & AlgorithmsTechnical Screen
• SquarepointMedium·Data Scientist
  Estimate Market Beta from Aligned Asset and Benchmark Returns

  Define market beta, identify the benchmark data needed beyond a stock's returns, and explain regression estimation and uncertainty.

  Statistics & MathTechnical Screen
• SquarepointMedium·Data Scientist
  Explain Linear Regression Assumptions, Evaluation, and Feature Addition

  Explain least-squares regression, inference assumptions, evaluation metrics, and why added features affect training and test R-squared differently.

  Machine LearningTechnical Screen
• SquarepointMedium·Data Scientist
  Explain derivatives, YTM, and core statistics

  This problem tests your understanding of fundamental financial math concepts (derivatives and YTM) and your ability to apply statistical rigor when modeling financial data.

  Statistics & MathTechnical ScreenFinanceStatisticsDerivatives
• SquarepointMedium·Data Scientist
  Fewest Increment-All-but-One Moves to Make Array Values Equal

  From a Squarepoint technical screen: one move adds 1 to every element of an integer array except one chosen element, and you must find the fewest moves that make all elements equal. It tests reasoning about what each move really changes, along with negative values and answers beyond the 32-bit range.

  Coding & AlgorithmsTechnical Screen
• SquarepointMedium·Data Scientist
  Find the Probability That Two Uniform Variables Have Product Above One-Half

  Compute the probability that two independent uniform variables have product above one-half by conditioning or integrating over the unit square.

  Statistics & MathTechnical Screen
• SquarepointMedium·Data Scientist
  Implement drawdown, single-trade profit, coin change

  This question evaluates a candidate's algorithmic problem-solving skills across array and time-series processing, greedy optimization, and dynamic programming, requiring implementation and complexity analysis of maximum drawdown, single-trade profit, and coin change problems within the Coding & Algorithms domain for a Data Scientist role.

  Coding & AlgorithmsTechnical Screen
• SquarepointHard·Data Scientist
  Maximize profit from one or many stock trades

  This question evaluates algorithmic problem-solving skills, particularly efficient array processing and profit-optimization across single-transaction and multiple-transaction variants, along with time and space complexity analysis.

  Coding & AlgorithmsTechnical Screen
• StripeMedium·Data Scientist
  Choose threshold under costs and uncertainty

  This question evaluates cost-sensitive threshold selection, uncertainty quantification for expected profit, calibration diagnostics, and population drift detection in a data science setting.

  Statistics & MathTechnical Screen
• StripeMedium·Data Scientist
  Compute power and interpret uplift metrics

  This question evaluates a Data Scientist's practical and conceptual competencies in A/B test design and analysis within the Statistics & Math domain, covering power/sample-size calculations, binary outcome inference, CUPED variance reduction, multiple-testing adjustments, and handling clustered/geographical data.

  Statistics & MathTechnical Screen