Data Scientist Interview Questions

Showing 121–150 of 163 results

• SIG (Susquehanna)Easy·Data Scientist
  Find Expected Spins Until Two Regions Appear

  This problem tests knowledge of expected value and geometric distributions by calculating the expected number of trials to observe two distinct outcomes from a discrete probability distribution.

  Statistics & MathOnline AssessmentProbabilityExpected ValueGeometric Distribution
• SIG (Susquehanna)Easy·Data Scientist
  Find a Green Triangle's Weight in a Balanced Mobile

  Solve a nested balanced-mobile puzzle and determine the green triangle's weight from a 160-pound total. The worked derivation uses an explicit equal-arm, massless-bar assumption, propagates whole-submobile weights upward, and explains why the left branch alone fixes the answer at 10 pounds.

  Statistics & MathOnline Assessment
• SIG (Susquehanna)Medium·Data Scientist
  Find probability of overlapping blooms

  This question evaluates understanding of probability theory, specifically reasoning about continuous uniform distributions, geometric probability, and the likelihood of overlap between random time intervals within a fixed horizon.

  Statistics & MathOnline Assessment
• SIG (Susquehanna)Easy·Data Scientist
  Find the Expected Number of Consecutive Chosen Pairs

  Calculate the expected number of consecutive pairs in a uniformly chosen subset of integers using indicator variables and linearity of expectation.

  Statistics & MathOnline Assessmentprobabilitycombinatoricsexpected-value
• SIG (Susquehanna)Easy·Data Scientist
  Find the Probability Two Muffins Are Sufficient

  This problem tests binomial probability distributions and the cumulative probability of independent discrete events.

  Statistics & MathOnline AssessmentProbabilityBinomial DistributionStatistics
• SIG (Susquehanna)Easy·Data Scientist
  Find the Success Probability of Bold Betting

  Calculate the chance of reaching five tokens before ruin under a bold, state-dependent betting rule. The solution enumerates the transitions, sets absorbing boundaries, solves the four-state recurrence for win probability one-third, and obtains 15/77 from an initial fortune of two.

  Statistics & MathOnline Assessment
• SIG (Susquehanna)Easy·Data Scientist
  Infer posterior after losing pick

  This question evaluates a candidate's understanding of conditional probability and posterior inference, assessing the ability to update probability estimates after observing that a chosen option did not occur.

  Statistics & MathOnline Assessment
• SIG (Susquehanna)Easy·Data Scientist
  Resolve Two Knights-and-Knaves Statements

  This question tests logical deduction and systematic case analysis under binary truth constraints.

  Statistics & MathOnline AssessmentLogicPuzzlesDiscrete Math
• SIG (Susquehanna)Easy·Data Scientist
  Solve Barn Animal Counts from Total Legs

  Tests setting up and solving a system of linear equations from verbal constraints using substitution to determine integer entity counts.

  Statistics & MathOnline Assessmentmathalgebraquantitative-reasoning
• SIG (Susquehanna)Easy·Data Scientist
  Solve animals-and-legs count

  This question evaluates a candidate's ability to translate a word problem into a system of linear equations and perform basic algebraic manipulation and arithmetic to determine unknown quantities.

  Statistics & MathOnline Assessment
• SIG (Susquehanna)Medium·Data Scientist
  Solve relative-truth cat puzzle

  This question evaluates logical deduction, constraint satisfaction, and quantitative manipulation of percentages and averages within a relative truth/lie framework, and is categorized under Statistics & Math and discrete logic puzzles.

  Statistics & MathOnline Assessment
• SIG (Susquehanna)Easy·Data Scientist
  Use Bayes for factory identification

  This question evaluates understanding of Bayesian inference and conditional probability by asking for the posterior probability that two observed black widgets originated from a specific factory.

  Statistics & MathOnline Assessment
• SSchonfeldMedium·Data Scientist
  Compute probability last passenger gets own seat

  This question evaluates a candidate's understanding of probability theory, combinatorics, and reasoning about sequential random processes, with emphasis on symmetry and conditional dependence.

  Coding & AlgorithmsOnline Assessment
• SSchonfeldMedium·Data Scientist
  Find smallest N for 5-and-21 sums

  This question evaluates understanding of integer linear combinations and elementary number theory, framed as a Frobenius coin problem that examines representability using non-negative multiples of 5 and 21.

  Coding & AlgorithmsOnline Assessment
• SquarepointMedium·Data Scientist
  Maximize revenue from inventory sales

  This question evaluates algorithmic problem-solving and optimization competencies focused on dynamic resource allocation, revenue maximization, and designing efficient solutions that scale with large n, m, and quantities.

  Coding & AlgorithmsOnline Assessment
• StripeHard·Data Scientist
  Design a model for subscription adoption prediction

  This question evaluates a candidate's ability to design and productionize a supervised machine-learning pipeline for predicting subscription adoption, testing competencies in labeling strategy, leakage identification and prevention, feature engineering from transactional and merchant metadata, model selection and calibration, evaluation with time-based validation, and post-deployment monitoring. It is commonly asked in the Machine Learning domain for Data Scientist roles because it assesses practical application and production-ready design along with conceptual understanding of time-based splits, class imbalance, performance metrics, and drift detection.

  Machine LearningOnline Assessment
• StripeMedium·Data Scientist
  Prioritize a 6-hour take-home effectively

  This question evaluates a candidate's ability to scope and time-box work, prioritize analyses and features, articulate trade-offs and risks, and produce concise deliverables under a tight deadline, reflecting judgment and leadership competencies for a Data Scientist.

  Behavioral & LeadershipOnline Assessment
• StripeMedium·Data Scientist
  Write SQL to detect recurring non-subscription users

  This question evaluates a candidate's ability to perform advanced SQL data manipulation and temporal pattern detection in transactional datasets, including attribute-based matching (amount and card fingerprint) and filtering by transaction status.

  Data Manipulation (SQL/Python)Online Assessment
• TikTokMedium·Data Scientist
  Count buggy vs non-buggy by employer

  This question evaluates proficiency in SQL data manipulation—particularly conditional aggregation and join semantics—for counting categorized records across related tables in a data science context.

  Data Manipulation (SQL/Python)Online Assessment
• TikTokMedium·Data Scientist
  Maximize Distinct Purchases Within Budget Constraints

  This question evaluates understanding of selection and optimization under budget constraints, algorithmic efficiency, and the ability to implement correct logic for maximizing the number of distinct items purchased.

  Coding & AlgorithmsOnline Assessment
• TikTokMedium·Data Scientist
  Maximize products bought under budget

  This question evaluates algorithmic problem-solving skills including sorting, prefix-sum accumulation, binary search, greedy selection, careful tie-breaking for lexicographic order, and complexity analysis.

  Coding & AlgorithmsOnline Assessment
• TikTokMedium·Data Scientist
  Select max-discount product per category

  This question evaluates proficiency in data manipulation and SQL querying—specifically use of window functions versus set-based alternatives, group-level ranking and tie-breaking, NULL-aware expressions, and numeric precision when computing discounts within the Data Manipulation (SQL/Python) domain.

  Data Manipulation (SQL/Python)Online Assessment
• Two SigmaMedium·Data Scientist
  Analyze NYC taxi trips efficiently over last 7 days

  This question evaluates proficiency in time-series filtering, relational joins, grouped aggregations (median and high-percentile calculations), numeric stability of percentile methods, and performance-aware vectorized data manipulation using SQL or pandas.

  Data Manipulation (SQL/Python)Online Assessment
• Two SigmaMedium·Data Scientist
  Analyze Temperatures and Update Regression

  This question evaluates proficiency in time-series and statistical analysis (defining volatility and similarity metrics), supervised regression modeling with mean squared error evaluation, greedy feature selection, and streaming/no-intercept linear regression updates.

  Machine LearningOnline Assessment
• Two SigmaMedium·Data Scientist
  Compute Piecewise Linear Interpolation

  This question evaluates skills in algorithm design and numerical interpolation, including sorting and searching among 2D points, handling boundary cases for extrapolation, and computing linear interpolation accurately and efficiently.

  Coding & AlgorithmsOnline Assessment
• Two SigmaMedium·Data Scientist
  Evaluate Piecewise Linear Function

  This question tests the ability to efficiently search through sorted interval data and apply linear interpolation to compute the value of a continuous piecewise function at a specific input point.

  Coding & AlgorithmsOnline AssessmentBinary SearchInterpolationData Structures
• Two SigmaMedium·Data Scientist
  Evaluate a Piecewise Linear Function

  This question tests the ability to efficiently search through a sorted collection of coordinates and apply linear interpolation to compute values for a continuous piecewise function.

  Coding & AlgorithmsOnline AssessmentBinary SearchInterpolationGeometry
• Two SigmaMedium·Data Scientist
  Evaluate piecewise linear function at x

  This question evaluates competency in numerical interpolation and handling of piecewise linear functions, including locating the correct segment in a sorted sequence of points and managing out-of-range inputs.

  Coding & AlgorithmsOnline Assessment
• Two SigmaEasy·Data Scientist
  Fill Missing Time-Series Values with Linear Interpolation (Duplicate Timestamps Allowed)

  This question evaluates a candidate's ability to perform time-series data cleaning and aggregation of duplicate timestamps, plus numerical linear interpolation and boundary value propagation, within the Coding & Algorithms domain.

  Coding & AlgorithmsOnline Assessment
• Two SigmaMedium·Data Scientist
  Perform no-intercept linear regression from two datasets

  This question evaluates linear regression modeling, numerical linear algebra (normal equations and stable factorization methods), regularization, R² interpretation, and data-preprocessing/validation skills within the Machine Learning domain for a Data Scientist role.

  Machine LearningOnline Assessment