Data Scientist Interview Questions

Showing 31–60 of 163 results

• BByteDanceEasy·Data Scientist
  Implement several OA simulation problems

  This set of problems evaluates skills in string processing, memory simulation and allocation logic, and online data-structure maintenance for dynamic contiguous segment counting, testing algorithmic design and attention to stateful invariants.

  Coding & AlgorithmsOnline Assessment
• C3 AIMedium·Data Scientist
  Choose a Parameter to Reduce Underfitting in Gradient-Boosted Trees

  Explain why decreasing minimum observations per leaf can reduce gradient-boosted tree underfitting and how to validate the change.

  Machine LearningOnline Assessment
• C3 AIMedium·Data Scientist
  Compare How Models Respond to Multicollinearity

  Compare multicollinearity effects in regression, Lasso, logistic regression, decision trees, and boosted trees without overstating immunity.

  Machine LearningOnline Assessment
• C3 AIMedium·Data Scientist
  Explain Training R-Squared After Adding a Random Feature

  Prove that ordinary training R-squared cannot decrease when adding a feature, while adjusted and test-set R-squared can.

  Statistics & MathOnline Assessment
• C3 AIMedium·Data Scientist
  Explain the Margin View of Boosting Classification

  Understand boosting classification through sequential learners, signed margins, surrogate losses, and the limits of training-margin claims.

  Machine LearningOnline Assessment
• C3 AIMedium·Data Scientist
  Identify What Does Not Fix Vanishing Gradients

  Explain why raising the learning rate does not fix vanishing gradients and compare skip connections, ReLU, and batch normalization.

  Machine LearningOnline Assessment
• CVS HealthMedium·Data Scientist
  Build a leak-free sklearn churn pipeline

  This question evaluates practical competencies in building a reproducible scikit-learn churn prediction pipeline—covering temporal splitting to avoid leakage, preprocessing, calibration, hyperparameter tuning, evaluation with ROC AUC/PR AUC and F1-based thresholds, and permutation feature importance—and is in the Machine Learning domain.

  Machine LearningOnline Assessment
• CVS HealthMedium·Data Scientist
  Compute A/B significance, CI, and power

  This question evaluates proficiency in statistical inference for A/B testing—specifically two-proportion z-tests, construction of confidence intervals with unpooled standard errors, sample-size and power calculations, and multiple-comparison correction via Bonferroni.

  Statistics & MathOnline Assessment
• CVS HealthMedium·Data Scientist
  Create Views, Insert, and Update Correctly

  This question evaluates SQL data-manipulation competencies including view creation, aggregate joins, INSERT/UPDATE operations, and reasoning about temporal effects on computed aggregates such as historical customer spend.

  Data Manipulation (SQL/Python)Online Assessment
• CVS HealthMedium·Data Scientist
  Create and query an e-commerce schema

  This question evaluates SQL schema design and data manipulation competencies, including defining PostgreSQL table types and constraints, inserting exact datasets, composing aggregate and join queries with date-based filters, and performing DML updates with verification.

  Data Manipulation (SQL/Python)Online Assessment
• CVS HealthMedium·Data Scientist
  Implement R² and Compare PCA With/Without Scaling

  This question evaluates a candidate's proficiency with regression evaluation metrics and linear-algebra-based dimensionality reduction, specifically implementing a numerically robust R² scorer and performing PCA with and without feature standardization using NumPy.

  Machine LearningOnline Assessment
• Capital OneMedium·Data Scientist
  Aggregate exam scores with NULL handling

  This question evaluates proficiency in SQL data manipulation, specifically joins (including LEFT JOIN behavior), NULL handling with ISNULL/COALESCE, conditional aggregation, distinct counts, and date-based filtering within the Data Manipulation (SQL/Python) domain, focusing on practical application of query-writing skills.

  Data Manipulation (SQL/Python)Online Assessment
• Capital OneMedium·Data Scientist
  Analyze 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 OneMedium·Data Scientist
  Compute and interpret 95% confidence intervals

  This question evaluates proficiency with confidence intervals, hypothesis testing for proportions and means, multiple-comparison adjustment (Bonferroni), and sample size calculations, including assessment of normal-approximation versus Wilson score methods.

  Statistics & MathOnline Assessment
• Capital OneHard·Data Scientist
  Design and analyze ad A/B test

  This question evaluates a candidate's competency in online experimentation and statistical analysis, covering hypothesis formulation, variance reduction, clustering and stratification, multiplicity control, power/MDE calculation, and operational metric guardrails.

  Analytics & ExperimentationOnline Assessment
• Capital OneHard·Data Scientist
  Design and analyze ads A/B test this week

  This question evaluates experimental design and applied statistical analysis skills for A/B testing, covering randomization, exposure control, stratification, variance reduction methods, metric formalization, hypothesis testing, sample sizing, sequential monitoring, diagnostics, and handling delayed offline conversions.

  Analytics & ExperimentationOnline Assessment
• Capital OneMedium·Data Scientist
  Find top category per region in Aug 2025

  This question evaluates proficiency in SQL data manipulation skills such as joining related tables, aggregating revenue, filtering by date and status, and implementing deterministic tie-breaking for categories.

  Data Manipulation (SQL/Python)Online Assessment
• Capital OneMedium·Data Scientist
  Fix dash dates and aggregate watch time

  This question evaluates data-cleaning and aggregation competencies, focusing on handling nonstandard missing-date markers, forward-filling in spreadsheets, correct date-range filtering, pivot-table summarization, and concise pandas grouping and aggregation.

  Data Manipulation (SQL/Python)Online Assessment
• Capital OneMedium·Data Scientist
  Merge CSVs and build revenue pivot with pandas

  This question evaluates proficiency in data manipulation and ETL using pandas, covering robust file I/O, join/merge semantics, null/coalescing behavior, date parsing, aggregation, and pivoting.

  Data Manipulation (SQL/Python)Online Assessment
• Capital OneMedium·Data Scientist
  Merge ad CSVs and compute CTR

  This question evaluates SQL data manipulation competencies such as cleaning and merging CSVs, forward-filling missing dates, correct multi-table joins without duplication, use of window functions, time-windowed aggregations, and computation of click-through rate (CTR).

  Data Manipulation (SQL/Python)Online Assessment
• Capital OneMedium·Data Scientist
  Resolve a Mismatch Between Regression and Classification Metrics

  Tests your ability to diagnose modeling and metric mismatches in credit risk and fraud scenarios, design proper two-stage architectures, and select evaluation metrics aligned with business decisions.

  Machine LearningOnline Assessmentmachine-learningmodel-evaluationregression
• CitadelHard·Data Scientist
  Build a regression model for wind power output

  This question evaluates competency in feature engineering, physics-informed regression modeling, sensor-data quality handling, model selection and validation, and uncertainty estimation for turbine-level instantaneous power prediction.

  ML System DesignOnline Assessment
• CitadelHard·Data Scientist
  Design a time-series home-buy decision classifier

  This question evaluates competency in ML system design for time-series decisioning, including rigorous target and horizon definition, temporal feature engineering, time-aware validation, probabilistic calibration and thresholding, leakage controls, model selection trade-offs, and deployment monitoring.

  ML System DesignOnline Assessment
• CCitibankMedium·Data Scientist
  Compute expected payoff of reroll dice game

  This question evaluates understanding of probability theory and expected-value computation in stopping-time processes, including conditioning and infinite-series reasoning, and also tests modeling of per-trial costs and break-even analysis.

  Statistics & MathOnline Assessment
• CCitibankMedium·Data Scientist
  Price options and bonds via binomial no-arbitrage

  This question evaluates competence in no-arbitrage pricing, risk-neutral valuation, early-exercise features of American versus European options, and short-rate tree bond valuation within the Statistics & Math domain.

  Statistics & MathOnline Assessment
• CoinbaseMedium·Data Scientist
  Solve Aptitude Test: Logical, Numerical, Verbal Reasoning

  This question evaluates logical, numerical, and verbal reasoning along with rapid pattern recognition and time-limited decision-making relevant to pre-employment aptitude screens for data science roles.

  Coding & AlgorithmsOnline Assessment
• DatabricksMedium·Data Scientist
  Explain Linear Regression Feature Transformation Equivalence

  This interview question evaluates core ML concepts, assumptions, math intuition, training/evaluation trade-offs, and practical failure modes in a realistic interview setting. A strong answer for Explain Linear Regression Feature Transformation Equivalence states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  Machine LearningOnline Assessment
• FRFive RingsHard·Data Scientist
  Solve coin probability and Bayesian inference problems

  This question evaluates probabilistic reasoning, stochastic-process intuition (pattern waiting times and runs), expected-value calculations, and Bayesian parameter estimation competency.

  Statistics & MathOnline Assessment
• Goldman SachsEasy·Data Scientist
  Bound the Rank of BA Given Rank of AB

  Determine the set of possible values for the rank of the matrix product BA given that A and B are 4x4 real matrices and rank(AB) = 2. This question tests fundamental linear algebra inequalities involving matrix ranks and nullities.

  Statistics & MathOnline AssessmentLinear AlgebraMatrix TheoryRank Inequalities
• Goldman SachsEasy·Data Scientist
  Compute the Arc Length of a Curve

  Tests single-variable calculus fundamentals, specifically calculating the derivative, setting up the standard arc length integral, and evaluating it using substitution.

  Statistics & MathOnline Assessmentcalculusintegrationgeometry