Data Scientist Interview Questions

Showing 1561–1590 of 1971 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
• SamsungMedium·Data Scientist
  Estimate laptops in an office

  This question evaluates back-of-the-envelope estimation skills, quantitative reasoning, and the ability to state and justify assumptions when modeling real-world counts like devices.

  Statistics & MathHR Screen
• SamsungMedium·Data Scientist
  Plan parking demand for a retail store

  This question evaluates demand forecasting, capacity planning, causal inference, and experimental-design competencies within data science, focusing on translating business objectives into measurable metrics such as peak occupancy, overflow rate, lost visits, and return on investment.

  Analytics & ExperimentationHR Screen
• 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
• ShopifyMedium·Data Scientist
  Analyze Causes of November and June Shopify Traffic Spikes

  This interview question evaluates metric design, causal reasoning, experiment setup, diagnostics, SQL/statistical checks, and recommendations in a realistic interview setting. A strong answer for Analyze Causes of November and June Shopify Traffic Spikes states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  Analytics & ExperimentationOnsite
• ShopifyMedium·Data Scientist
  Analyze Pirate Theme Usage Growth Over Time

  This question evaluates a candidate's ability to perform SQL-based data manipulation and time-series analysis, emphasizing joins, aggregation, time-bucketing, and definition of growth metrics to measure feature adoption.

  Data Manipulation (SQL/Python)Technical Screen
• ShopifyMedium·Data Scientist
  Analyze Pirated Theme Usage

  Calculate monthly metrics on unlicensed theme usage and lost revenue by evaluating temporal interval overlaps between installation lifespans and calendar months.

  Data Manipulation (SQL/Python)Technical ScreenSQLPandasInterval Overlap
• ShopifyMedium·Data Scientist
  Analyze Pirated Theme Usage Impact

  This question evaluates a candidate's ability to perform data manipulation and analytics with SQL and Python to detect license compliance, construct month-level time windows, and quantify revenue impact from pirated theme usage.

  Data Manipulation (SQL/Python)Technical Screen
• ShopifyMedium·Data Scientist
  Analyze Trends to Optimize Pirate-Theme Product Strategy

  This interview question evaluates metric design, causal reasoning, experiment setup, diagnostics, SQL/statistical checks, and recommendations in a realistic interview setting. A strong answer for Analyze Trends to Optimize Pirate-Theme Product Strategy states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  Analytics & ExperimentationTechnical Screen
• ShopifyEasy·Data Scientist
  Answer Product DS HR Screen

  This prompt evaluates behavioral and leadership competencies for a product data scientist role, including product thinking, stakeholder management, communication, motivation, team composition and dynamics, and the ability to articulate business impact and role scope.

  Behavioral & LeadershipHR Screen
• ShopifyMedium·Data Scientist
  Assess Candidate's Remote Collaboration and Technical Proficiency

  Evaluates remote cross-functional collaboration and technical proficiency for a data-science role. Strong answers cover challenging projects, stakeholder rituals, async artifacts, tool stack, reproducibility, and quantified impact.

  Behavioral & LeadershipOnsite
• ShopifyMedium·Data Scientist
  Assess and push back on ideology-heavy interviews

  This question evaluates a candidate's competency in cultural fit assessment, evidence-backed critique, concise written and verbal communication, prioritization under time pressure, and the ability to design escalation and interview strategies.

  Behavioral & LeadershipTechnical Screen
• ShopifyMedium·Data Scientist
  Calculate Jaccard Similarity Score for Two String Lists

  This question evaluates understanding of similarity metrics and competency in comparing string collections, reflecting knowledge of set-theoretic concepts and manipulation of collection data structures used in data processing.

  Coding & AlgorithmsOnsite
• ShopifyMedium·Data Scientist
  Calculate Week-over-Week Revenue Change Using SQL

  This question evaluates proficiency in SQL time-series aggregation, weekly grouping, and prior-period comparison for calculating percentage changes in revenue.

  Data Manipulation (SQL/Python)Technical Screen
• ShopifyMedium·Data Scientist
  Compute Jaccard Similarity for Lists

  This question evaluates understanding of Jaccard similarity and set-based operations, assessing competency in deduplicating lists, precise string comparisons (case-sensitivity and whitespace), and handling edge cases.

  Coding & AlgorithmsTechnical Screen
• ShopifyMedium·Data Scientist
  Compute Theme Similarity

  This question tests the ability to implement a set-based similarity metric, specifically the Jaccard index, to compare collections of theme-related features.

  Coding & AlgorithmsTechnical ScreenData StructuresAlgorithmsSets
• ShopifyEasy·Data Scientist
  Deep dive a technical project and its impact

  This question evaluates a data scientist's ability to lead and execute end-to-end technical projects, including problem framing, data sourcing and quality, modeling and experimentation, deployment and monitoring, and quantifying business impact.

  Behavioral & LeadershipTechnical Screen
• ShopifyMedium·Data Scientist
  Describe Your Professional Growth and Key Learning Experiences

  This interview question evaluates behavioral evidence, ownership, communication, trade-offs, and measurable outcomes in a realistic interview setting. A strong answer for Describe Your Professional Growth and Key Learning Experiences states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  Behavioral & LeadershipTechnical Screen