Statistics & Math Interview Questions

Showing 151–180 of 218 results

• PayPalHard·Data Scientist
  Interpret p-values and common pitfalls

  Evaluates interpretation of p-values, hypothesis testing, experimental design and statistical pitfalls in a fraud/experimentation context—including concepts like effect size, statistical power, multiple comparisons, delayed/rare outcomes, and imperfect randomization; category/domain: Statistics & Math.

  Statistics & MathTechnical Screen
• Point72Hard·Quantitative Researcher
  Derive the Optimal Bid in a Two-Bidder Second-Price Auction

  Two risk-neutral bidders compete for one item in a sealed-bid second-price auction. Explain the assumptions and derivation clearly, check edge cases, and show how the result changes when those assumptions no longer hold.

  Statistics & MathTechnical Screen
• Point72Hard·Quantitative Researcher
  Find the Two Heaviest Balls with Minimum Comparisons

  There are 32 balls with distinct weights. Explain the assumptions and derivation clearly, check edge cases, and show how the result changes when those assumptions no longer hold.

  Statistics & MathTechnical Screen
• Point72Medium·Quantitative Researcher
  Prove That Lasso Can Be Written as a Quadratic Program

  Derive the Lasso quadratic-program formulation and prove equivalence, convexity, minimizer correspondence, and rank-related uniqueness.

  Statistics & MathTechnical Screen
• Point72Medium·Quantitative Researcher
  Solve Three Probability Models

  Solve three independent probability questions. Explain the assumptions and derivation clearly, check edge cases, and show how the result changes when those assumptions no longer hold.

  Statistics & MathTechnical Screen
• RedditHard·Data Scientist
  Justify synthetic control and handle inference

  This question evaluates understanding of synthetic control methodology, causal identification assumptions, estimation and regularization choices, inference techniques for pointwise and cumulative effects, and diagnostic checks for panel time-series interventions.

  Statistics & MathTechnical Screen
• RobloxMedium·Data Scientist
  Derive variance and CTR confidence intervals

  This problem tests your understanding of statistical inference for binomial proportions, specifically calculating confidence intervals for Click-Through Rates (CTR) and understanding how to aggregate variability across multiple days.

  Statistics & MathTechnical ScreenStatisticsInferenceCTR
• RobloxHard·Data Scientist
  Implement robust one/two-sided p-value function

  This question evaluates proficiency in statistical hypothesis testing, numerical computing, and numerical stability when implementing p-value calculations for z and t distributions, and it targets the Statistics & Math domain for a data scientist role.

  Statistics & MathTechnical Screen
• RRokuEasy·Data Scientist
  Explain Bias-Variance Trade-off Simply for Stakeholders

  Evaluates the ability to explain the bias-variance trade-off to non-technical stakeholders. Strong answers define bias as underfitting, variance as overfitting, use a clear analogy, and explain why models must generalize to new data rather than memorize training data.

  Statistics & MathTechnical Screen
• SIG (Susquehanna)Medium·Data Scientist
  Analyze Knights-and-Knaves Dialogue Variants

  Analyze Knights-and-Knaves Dialogue Variants evaluates statistical assumptions, formulas, estimation strategy, uncertainty, edge cases, and interpretation in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  Statistics & MathTechnical Screen
• SIG (Susquehanna)Hard·Data Scientist
  Compute answers to probability and counting puzzles

  This problem tests your ability to model sequential probabilistic events using combinatorics and conditional probability, specifically requiring the calculation of expected outcomes in a game of chance.

  Statistics & MathTechnical ScreenProbabilityExpectationCombinatorics
• SIG (Susquehanna)Easy·Data Scientist
  Determine knights and knaves roles

  This interview question evaluates statistical assumptions, formulas, estimation strategy, uncertainty, edge cases, and interpretation in a realistic interview setting. A strong answer for Determine knights and knaves roles states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  Statistics & MathTechnical Screen
• ShopifyMedium·Data Scientist
  Perform no-calculator math accurately and fast

  This question evaluates mental arithmetic, rapid estimation, numerical bounds, and familiarity with exponentials and square-root approximations within the Statistics & Math category for a Data Scientist role.

  Statistics & MathTechnical Screen
• 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
  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
• SnapchatMedium·Software Engineer
  Explain median vs mean for L1/L2

  This question evaluates understanding of central tendency and loss functions—specifically the roles of median and mean under L1 (absolute) and L2 (squared) norms—and the geometric extension of these concepts to two-dimensional data.

  Statistics & MathTechnical Screen
• 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
• 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
  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 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·Software Engineer
  Find the Correlation Between Two Die-Face Counts

  A fair six-sided die is rolled independently `n` times, where `n` is a fixed positive integer. Explain the assumptions and derivation clearly, check edge cases, and show how the result changes when those assumptions no longer hold.

  Statistics & MathTechnical 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
• StackAdaptEasy·Machine Learning Engineer
  Explain Why a Geometric Mean Can Exceed Its Median

  Tests derivation and comparison of the expected value and median of a geometric distribution, explaining how right-skewness drives the mean above the median across different parameterizations.

  Statistics & MathTechnical Screenprobabilitystatisticsgeometric-distribution
• 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
• TTekionMedium·Software Engineer
  Count Open Lockers After 100 Rounds

  This problem tests mathematical reasoning and pattern recognition, specifically the relationship between integer divisors and toggling operations.

  Statistics & MathTechnical ScreenMathematicsNumber TheoryPattern Recognition
• TTekionMedium·Software Engineer
  Find an Optimal Strategy for an Even-Row Coin Game

  Analyze optimal play in an even-row coin game, using position parity and game values to distinguish a guaranteed tie from a strict first-player win.

  Statistics & MathTechnical Screen
• TeslaHard·Machine Learning Engineer
  Explain and derive importance sampling estimators

  This question evaluates understanding of importance sampling, Monte Carlo estimators, weight normalization, variance behavior, optimal proposal selection, and effective sample size, assessing competency in statistical estimation and Monte Carlo methods.

  Statistics & MathTechnical Screen
• TikTokEasy·Data Scientist
  Calculate Expected Draws for X > 0.8 in Uniform(0,1)

  This interview question evaluates statistical assumptions, formulas, estimation strategy, uncertainty, edge cases, and interpretation in a realistic interview setting. A strong answer for Calculate Expected Draws for X > 0.8 in Uniform(0,1) states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  Statistics & MathTechnical Screen