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Data Scientist Interview Questions

Practice 9403 coding, system design and machine learning questions from 546 companies, sorted by role, topic and interview round. Every question has step-by-step hints, a code runner that supports 8 languages and an AI mentor; members also get the full solution walkthrough.

9403
Questions
546
Companies
11
Topics
8
Languages

Showing 151–163 of 163 results

  • WayfairEasyData Scientist
    Clean scores and return top 5 students

    This problem tests your ability to clean tabular data by performing conditional imputation and applying window functions to rank performance metrics.

    Data Manipulation (SQL/Python)Online AssessmentPandasData CleaningImputation
  • WayfairEasyData Scientist
    Derive insights and improve complaint resolutions

    This problem tests the ability to join disparate datasets to identify trends, evaluate the effectiveness of resolution strategies, and design an A/B test to validate potential improvements in customer satisfaction.

    Analytics & ExperimentationOnline AssessmentSQLCausal InferenceA/B Testing
  • WayfairEasyData Scientist
    Find top buyer in earliest 10-year window

    This question tests the ability to filter data by date ranges, group transactional records by user, and use window functions or aggregations to identify a specific record based on criteria.

    Data Manipulation (SQL/Python)Online AssessmentSQLAggregationWindow Functions
  • WayfairEasyData Scientist
    How to improve complaint resolution

    This question evaluates a candidate's competency in data-driven analytics, causal inference, metrics design, and experimentation for customer support performance.

    Analytics & ExperimentationOnline Assessment
  • WayfairEasyData Scientist
    Solve SQL and Python OA tasks

    This question evaluates SQL and pandas data-manipulation skills, including joined aggregations over date windows, handling of missing values with median imputation, and multi-criteria sorting and tie-breaking.

    Data Manipulation (SQL/Python)Online Assessment
  • WaymoMediumData Scientist
    Analyze User Ride Activity with SQL

    Solve four SQL analytics tasks on ride and user tables: inactive users, monthly rides and ratings, low-frequency users by city, and first-versus-third active-month ratings. The walkthrough emphasizes outer joins, date boundaries, aggregation grain, window functions, and weighted averages.

    Data Manipulation (SQL/Python)Online Assessment
  • WaymoMediumData Scientist
    Assess Routing Experiment Validity

    This question evaluates experimental analysis and statistical hypothesis testing skills, including data preparation and joining, interpretation of p-values, and understanding of causal inference and threats to validity in A/B tests.

    Statistics & MathOnline Assessment
  • WaymoMediumData Scientist
    Compute Ride Metrics in SQL

    This question evaluates SQL data manipulation skills, covering joins between normalized tables, timezone-aware date filtering and calendar-month grouping, aggregation and NULL-aware averages, counting distinct and inactive users, and cohort/retention analysis.

    Data Manipulation (SQL/Python)Online Assessment
  • WaymoMediumData Scientist
    Evaluate Smart Wait Launch Impact

    This question evaluates a data scientist's competencies in causal inference and experiment analysis, including interpreting A/B test outcomes, trade-offs between conversion and operational metrics, selection of primary and guardrail metrics, and generation of alternative hypotheses.

    Analytics & ExperimentationOnline Assessment
  • WaymoMediumData Scientist
    Implement Safe Average Function

    This question evaluates proficiency with basic programming fundamentals including numeric computation, handling edge cases such as empty inputs, input immutability, and data type consistency.

    Coding & AlgorithmsOnline Assessment
  • WaymoMediumData Scientist
    Implement a Safe Average Function in Python

    Implement a Python average function that returns zero for an empty list and explain its time and space complexity. Clarify numeric types, missing values, NaN behavior, streaming alternatives, precision concerns, and the tests needed for a reliable data utility.

    Data Manipulation (SQL/Python)Online Assessment
  • WaymoMediumData Scientist
    Interpret a Smart Wait Launch with Conflicting Metrics

    Interpret a product launch where conservative wait estimates reduce conversion while observed pickup time also falls. Diagnose selection effects and alternative causes, define customer and fleet metrics with consistent denominators, and propose an experiment that can separate display accuracy from operational improvement.

    Analytics & ExperimentationOnline Assessment
  • WaymoMediumData Scientist
    Test Whether a Routing Experiment Reduced Pickup Time

    Analyze a routing A/B test in Python by filtering and joining user and ride data, then calculating a Welch t-test for pickup time. Interpret effect size and uncertainty, address repeated rides and post-treatment selection, and design stronger user-level or cluster-aware inference.

    Analytics & ExperimentationOnline Assessment