Statistics & Math interview questions

Showing 391–420 of 439 results

• Analyze Cancellation Change with StatisticsMedium

  This question evaluates statistical inference for binary outcomes, regression adjustment for confounding, experiment design and power analysis, and nonparametric uncertainty estimation using bootstrapping, and is targeted at Data Scientist roles within the Statistics & Math domain.

  UberData ScientistStatistics & MathTechnical Screen
• Apply instrumental variables under interferenceHard

  This question evaluates understanding of causal inference with instrumental variables in the presence of interference, testing skills in defining units and aggregation levels for market‑level spillovers, articulating IV assumptions (relevance, exclusion restriction, independence, monotonicity), and formulating estimation frameworks such as two‑stage least squares. Commonly asked in Statistics & Math interviews for data scientist roles because networked marketplaces invalidate simple A/B tests, it sits in the econometrics/causal inference domain and primarily assesses practical application of IV methods while requiring conceptual understanding of identification, robustness diagnostics, and sensitivity analysis.

  UberData ScientistStatistics & MathTechnical Screen
• Compare Two Coin ProportionsMedium

  This question evaluates proficiency in statistical inference for proportions, including hypothesis formulation, comparison of two independent samples, confidence interval interpretation, and interpretation of p-values and sampling variability.

  UberData ScientistStatistics & MathTechnical Screen
• Compute A/B sample size under clusteringHard

  This question evaluates competency in experimental design and statistical inference for A/B testing, specifically sample size calculation for two-sample proportions with unequal allocation, clustering effects (ICC and design effect), and adjustments for bot removal and data-quality attrition.

  UberData ScientistStatistics & MathTechnical Screen
• Derive a CDF from a PDFMedium

  This question tests the ability to derive a Cumulative Distribution Function (CDF) from a given Probability Density Function (PDF), ensuring proper integration and boundary conditions.

  UberData ScientistStatistics & MathTechnical Screen
• Design an A/B test; choose Z vs THard

  This question evaluates a candidate's competency in experimental design and statistical inference, covering sample-size and power calculations, the choice between Z and T tests, sequential testing/alpha-spending strategies, and causal-inference planning for non-randomized rollouts.

  UberData ScientistStatistics & MathTechnical Screen
• Formulate OR model to reduce driver backtrackingMedium

  This question evaluates skills in defining a quantitative driver-backtracking metric from GPS and assignment logs, detecting and validating backtracking segments, and formulating constrained optimization models for dispatch and repositioning, drawing on statistics, operations research, and stochastic optimization.

  UberData ScientistStatistics & MathOnsite
• Formulate hypotheses and compute AB test significanceHard

  This question evaluates a data scientist's competency in experimental design and statistical inference for A/B testing, covering hypothesis formulation, difference-in-proportions testing and confidence intervals, guardrail analysis, multiple-testing correction, interim alpha-spending approaches, and variance-reduction techniques such as CUPED.

  UberData ScientistStatistics & MathTechnical Screen
• Measure rider incentive causal ROIHard

  This question evaluates a data scientist's competency in causal inference and experimental design, marketplace health metric construction, ROI estimation, and the handling of selection bias, spillover effects, multiple testing, and heterogeneity in two-sided platforms.

  UberData ScientistStatistics & MathTechnical Screen
• Should Uber double member discounts?Medium

  This problem tests your ability to design a controlled experiment for a two-sided marketplace and evaluate whether a discount-doubling strategy is statistically and economically viable.

  UberData ScientistStatistics & MathTechnical Screen
• Analyze HT vs HH stopping-time probabilitiesMedium

  This question evaluates understanding of discrete probability, stopping-time analysis, pattern occurrence in Bernoulli sequences, derivation of PMFs and expectations, and the ability to generalize results to biased coins.

  UpstartData ScientistStatistics & MathTechnical Screen
• Assess Probability of Heads in Coin TossesEasy

  Assess Probability of Heads in Coin Tosses 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.

  UpstartData ScientistStatistics & MathOnsite
• Calculate Expected Streaks in Coin Toss SequenceEasy

  Calculate Expected Streaks in Coin Toss Sequence 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.

  UpstartData ScientistStatistics & MathOnsite
• Calculate Particle Survival Probability After Time tEasy

  This interview question evaluates statistical assumptions, formulas, estimation strategy, uncertainty, edge cases, and interpretation in a realistic interview setting. A strong answer for Calculate Particle Survival Probability After Time t states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  UpstartData ScientistStatistics & MathTechnical Screen
• Combine noisy thermometers; compute random-walk correlationsEasy

  This question evaluates estimation and probabilistic reasoning skills, specifically the construction of unbiased estimators and variance-minimizing linear combinations for combining noisy measurements, together with computation and asymptotic characterization of correlations in a 2D simple random walk.

  UpstartData ScientistStatistics & MathOnsite
• Compute decay, OLS, and classic probability resultsEasy

  This question evaluates probability and statistical modeling skills—probabilistic reasoning for exponential decay and the coupon-collector expectation, derivation of population OLS coefficients for simple linear models, simulation implementation, and conditional probability reasoning exemplified by the Monty Hall scenario.

  UpstartData ScientistStatistics & MathOnsite
• Correct length-biased sampling from family-size surveyEasy

  This question evaluates understanding of length-biased sampling and inference under sampling bias, specifically how sampling by individuals (children) differs from sampling by households when estimating family-size probabilities.

  UpstartData ScientistStatistics & MathTechnical Screen
• Determine distribution of aX+b when X~N(0,1)Easy

  This problem tests your understanding of how linear (affine) transformations affect the properties of a normal distribution and the derivation of its mean and variance.

  UpstartData ScientistStatistics & MathHR Screen
• Estimate Family Proportions and Explain Regression AnomaliesMedium

  Estimate Family Proportions and Explain Regression Anomalies 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.

  UpstartData ScientistStatistics & MathOnsite
• Estimate and Derive Regression Coefficient for X on yMedium

  Estimate and Derive Regression Coefficient for X on y 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.

  UpstartData ScientistStatistics & MathOnsite
• Identify binomial model and compute momentsEasy

  This question tests the ability to identify a binomial process, express its probability mass function, and derive its fundamental moments (mean and variance).

  UpstartData ScientistStatistics & MathHR Screen
• Solve core probability/statistics mini-problemsMedium

  Category: Statistics & Math; this prompt evaluates core probability and statistical concepts — exponential decay and discrete survival counts, Bayesian updating, properties of population OLS coefficients, conditional-probability reasoning exemplified by Monty Hall, the coupon-collector expected time, and the conceptual distinction between likelihood and probability — relevant for Data Scientist roles. It is commonly asked because it probes foundational distributional intuition, independence and conditional inference, and expectation/estimation at an introductory-to-intermediate theoretical level that underpins applied modeling and experimental interpretation.

  UpstartData ScientistStatistics & MathOnsite
• Solve drunk-passenger probability and simulate outcomeMedium

  This question evaluates probabilistic reasoning and stochastic-process intuition, including use of invariant arguments, closed-form derivations, statistical estimation via Monte Carlo simulation, and analysis of algorithmic time and space complexity.

  UpstartData ScientistStatistics & MathTechnical Screen
• Approximate a Binomial Upper Tail with a Normal DistributionHard

  This question tests the application of the Normal approximation to the Binomial distribution, the use of continuity correction, and the ability to evaluate the error bounds of this approximation.

  Virtu FinancialQuantitative ResearcherStatistics & MathOnsite
• Approximate a Rare-Event Binomial ProbabilityHard

  This problem tests the application of the Poisson approximation to binomial distributions for rare events and the evaluation of the error bounds associated with this approximation.

  Virtu FinancialQuantitative ResearcherStatistics & MathOnsite
• Birthday Collisions and the Closest Pair of BirthdaysHard

  This problem tests your understanding of probability theory, specifically the generalized birthday paradox, and your ability to analyze spacing distributions of random variables.

  Virtu FinancialQuantitative ResearcherStatistics & MathOnsite
• Compare Two Strategies for Getting Ten Consecutive HeadsHard

  This problem tests your ability to model probability through recursion and expectation, specifically comparing the efficiency of two distinct strategies for achieving a target streak of coin tosses.

  Virtu FinancialQuantitative ResearcherStatistics & MathOnsite
• Compute probability in urn with green returnsMedium

  Compute probability in urn with green returns 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.

  Virtu FinancialData ScientistStatistics & MathTechnical Screen
• Compute probability with colored balls drawsMedium

  This interview question evaluates statistical assumptions, formulas, estimation strategy, uncertainty, edge cases, and interpretation in a realistic interview setting. A strong answer for Compute probability with colored balls draws states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  Virtu FinancialData ScientistStatistics & MathTechnical Screen
• Bound R-Squared for Individual and Combined OLS RegressionsMedium

  Derive in-sample OLS R-squared bounds and the joint-model range from individual scores, including intercept assumptions, predictor correlation, and out-of-sample exceptions.

  VoleonQuantitative ResearcherStatistics & MathTechnical Screen