Data Scientist Interview Questions

Showing 1051–1076 of 1076 results

• WeRideMedium·Data Scientist
  Test whether two distributions differ

  Test whether two datasets come from the same distribution using univariate and multivariate methods, including KS, categorical tests, classifier two-sample tests, MMD, permutation tests, effect sizes, multiple-testing control, clustering-aware uncertainty, and sampling designs.

  Statistics & MathTechnical Screen
• WAWeiss Asset ManagementMedium·Data Scientist
  Evaluate and Monitor a Paid Electricity Price Forecast

  This problem tests the ability to design an evaluation framework for time-series forecasting models and systematic troubleshooting of performance degradation in an automated trading pipeline.

  Analytics & ExperimentationTechnical ScreenTime SeriesBacktestingModel Evaluation
• Wells FargoHard·Data Scientist
  Core Components of an LLM-Based AI Agent and How They Interact

  An open question about AI agents asks you to name the components of an agent built around a language model, explain what each one does, and show how they work together to complete a multi-step task. It tests understanding of tools, memory, planning, control loops, guardrails and evaluation.

  Machine LearningTechnical Screen
• Wells FargoMedium·Data Scientist
  Design Excel visuals for risk results

  Design Excel visuals for risk results evaluates metric design, causal reasoning, experiment setup, diagnostics, SQL/statistical checks, and recommendations in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  Analytics & ExperimentationTechnical Screen
• Wells FargoMedium·Data Scientist
  Ensure model ethics and governance

  Ensure model ethics and governance evaluates behavioral evidence, ownership, communication, trade-offs, and measurable outcomes in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  Behavioral & LeadershipTechnical Screen
• Wells FargoMedium·Data Scientist
  Explain PD model validation steps

  Explain PD model validation steps evaluates core ML concepts, assumptions, math intuition, training/evaluation trade-offs, and practical failure modes in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  Machine LearningTechnical Screen
• Wells FargoHard·Data Scientist
  Organizing Code and Repositories: Functions, Classes, Comments, GitHub Files

  A software practice question asks how you organize code into functions, classes and files, how and when you write comments, and which files a GitHub repository should and should not contain. It tests modular design judgment, documentation habits, and reproducible, secure project hygiene.

  Software Engineering FundamentalsTechnical Screen
• Wells FargoHard·Data Scientist
  Research Deep Dive: Model Details, Coding Habits and Diffusion Architecture

  A research deep dive asks you to present a project under repeated follow-ups about the exact model you used and your coding habits, then explain how a diffusion model is built, trained and sampled. It tests ownership of your work, depth under probing, and command of noising, denoising networks and conditioning.

  Machine LearningTechnical Screen
• Wells FargoMedium·Data Scientist
  Write SQL for rolling default rates

  This question evaluates proficiency with SQL window functions and time-series aggregation, specifically the ability to compute rolling metrics across customer segments by aggregating defaults and accounts over a moving 12-month window.

  Data Manipulation (SQL/Python)Technical Screen
• WhatnotMedium·Data Scientist
  Calculate Monthly Customer Retention

  A PostgreSQL interview problem about calculating monthly customer retention from activity data. It tests month-level cohort construction, distinct-user counting, correct denominator selection, and handling customers who return across calendar boundaries.

  Data Manipulation (SQL/Python)Technical Screen
• WhatnotMedium·Data Scientist
  Compute a Seven-Day Rolling Average

  A PostgreSQL interview problem about computing a seven-day rolling average from dated observations. Candidates must use window frames carefully, preserve the requested grain, handle incomplete history, and return deterministically ordered results.

  Data Manipulation (SQL/Python)Technical Screen
• WhatnotMedium·Data Scientist
  Define Marketplace Success Metrics and Investigate Their Movement

  A product analytics interview about defining success for a two-sided marketplace and diagnosing an unexpected metric movement. It tests metric decomposition, cohort and funnel analysis, instrumentation checks, and the ability to separate product effects from mix shifts.

  Analytics & ExperimentationTechnical Screen
• WorldquantMedium·Data Scientist
  Find the Expected Number of Record Maxima

  A permutation of the distinct values `1` through `100` is revealed from left to right. Explain the assumptions and derivation clearly, check edge cases, and show how the result changes when those assumptions no longer hold.

  Statistics & MathTechnical Screen
• WorldquantMedium·Data Scientist
  Price a Sequential Four-Box Search Game

  Four boxes contain one \$100 prize. Explain the assumptions and derivation clearly, check edge cases, and show how the result changes when those assumptions no longer hold.

  Statistics & MathTechnical Screen
• YahooEasy·Data Scientist
  Calculate Expected Flips for Heads-Tails Sequence

  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 Flips for Heads-Tails Sequence states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  Statistics & MathTechnical Screen
• YahooMedium·Data Scientist
  Calculate Total Spend and Identify Key User Metrics

  This question evaluates a data scientist's proficiency in transactional data manipulation using SQL and Python, focusing on aggregation, ranking, joins, date arithmetic, and numeric rounding to produce user-level and time-series metrics.

  Data Manipulation (SQL/Python)Technical Screen
• YahooMedium·Data Scientist
  Evaluate Widget Impact on User Engagement with A/B Testing

  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 Evaluate Widget Impact on User Engagement with A/B Testing states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  Analytics & ExperimentationTechnical Screen
• YahooMedium·Data Scientist
  Merge words by head-tail chaining

  This question evaluates graph-theoretic reasoning and string-manipulation skills, focusing on the ability to reason about ordering constraints, edge cases like self-loops and multiple identical relationships, and traversal over relationships between items.

  Coding & AlgorithmsTechnical Screen
• YahooMedium·Data Scientist
  Prove Equal Probability Impossible with Relabeled Dice Faces

  This interview question evaluates statistical assumptions, formulas, estimation strategy, uncertainty, edge cases, and interpretation in a realistic interview setting. A strong answer for Prove Equal Probability Impossible with Relabeled Dice Faces states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  Statistics & MathTechnical Screen
• YahooMedium·Data Scientist
  Solve Data Structure Challenges with Python Algorithms

  This question evaluates proficiency in fundamental data structure manipulation and string-processing algorithms, specifically preserving insertion order during list deduplication and performing iterative overlap-based word merging.

  Coding & AlgorithmsTechnical Screen
• YYelpEasy·Data Scientist
  Estimate Experiment Duration with Power Analysis

  This question tests the ability to perform a power analysis to calculate sample size requirements for an A/B test and derive the experiment duration based on traffic constraints.

  Analytics & ExperimentationTechnical ScreenA/B TestingPower AnalysisStatistics
• YYelpEasy·Data Scientist
  Recommend a Decision After a Nonsignificant Experiment

  This question tests the ability to interpret nonsignificant experimental results and formulate data-driven business recommendations beyond simple hypothesis testing.

  Analytics & ExperimentationTechnical ScreenA/B TestingHypothesis TestingProduct Analytics
• YYelpEasy·Data Scientist
  Return Integers in Descending Ranked Order

  This problem tests the ability to manipulate lists and sort data while maintaining the relative order of duplicate elements using common programming patterns.

  Coding & AlgorithmsTechnical ScreenSortingArraysAlgorithms
• ZooxMedium·Data Scientist
  Compute posterior for biased coin after 3H1T

  This question evaluates a candidate's understanding of Bayesian inference, computation of posteriors and Bayes factors, posterior predictive probabilities, and decision-theoretic model selection in a simple biased-coin scenario.

  Statistics & MathTechnical Screen
• ZooxMedium·Data Scientist
  Describe resolving a high-stakes research disagreement

  This question evaluates a data scientist's competency in stakeholder communication, leadership in research contexts, and technical reasoning about research design and probability/statistics assumptions, and is categorized under Behavioral & Leadership.

  Behavioral & LeadershipTechnical Screen
• ZooxMedium·Data Scientist
  Design navigation-safety simulation parameters and experiments

  This problem tests your ability to design a high-reliability simulation framework using variance reduction techniques and statistical validation methods to evaluate rare-event autonomous driving scenarios.

  Machine LearningTechnical ScreenSimulationRare-Event-EstimationImportance-Sampling