Data Scientist Interview Questions

Showing 241–270 of 339 results

• PinterestMedium·Data Scientist
  Compute CTR by format for new US users

  This question evaluates a candidate's competency in SQL data manipulation and aggregation, covering joins, date-based filtering for user cohorts, deduplication, conditional summing, null-safe arithmetic, rounding, and ordering to compute a business metric (CTR).

  Data Manipulation (SQL/Python)Technical Screen
• PinterestMedium·Data Scientist
  Find the Share of Power Listeners per Region from Play Events

  Write a PostgreSQL query that, for a trailing 7-day window, classifies listeners per region as active or 'power' users based on how many distinct days they listened and whether they used at least three different playback devices on any single one of those days, then reports the power-user share per region.

  Data Manipulation (SQL/Python)Technical Screensqlwindow-functionsaggregation
• PinterestMedium·Data Scientist
  Find top video category by average time

  This question evaluates a candidate's ability to perform data manipulation and aggregation in Python (pandas), covering skills such as filtering, handling nulls and nonpositive values, mapping categorical IDs to names, rounding numerical results, and applying tie-breaking rules.

  Data Manipulation (SQL/Python)Technical Screen
• PinterestMedium·Data Scientist
  Implement Binary Search for Policy Violation Logs

  This question evaluates understanding of algorithmic search and data manipulation skills, specifically applying binary search over date-ordered logs and composing efficient queries using SQL and Python.

  Data Manipulation (SQL/Python)Onsite
• PinterestHard·Data Scientist
  Implement and Evaluate Pin Similarity in Python

  Practice a DS-focused Python similarity question using Pin representations, cosine similarity, top-k ranking, and explicit edge-case handling. Extend the implementation discussion to vectorized scaling, approximate retrieval, offline ranking metrics, leakage checks, diversity, and online evaluation.

  Data Manipulation (SQL/Python)Technical Screen
• PinterestMedium·Data Scientist
  Transform nested dicts with pandas apply/lambda

  This question evaluates proficiency in pandas-based data manipulation, including flattening nested list and dict structures, parsing nested attributes, computing per-user aggregates and segment metrics, and implementing robust, vectorized extraction logic that handles missing keys and avoids SettingWithCopy pitfalls.

  Data Manipulation (SQL/Python)Onsite
• PinterestMedium·Data Scientist
  Write Queries for Pinterest Engagement Tasks

  This question evaluates SQL-based data manipulation and Python set/co-occurrence computation skills, covering aggregation, joins, timestamp-based cohorting and windowing, freshness detection, CTR calculation, and similarity scoring within a data scientist context.

  Data Manipulation (SQL/Python)Technical Screen
• PinterestMedium·Data Scientist
  Write SQL to compute max-overlap lists

  This question evaluates proficiency in SQL data manipulation and set-based operations, focusing on deduplication, pairwise aggregation, and similarity metric computation (Jaccard) over relational tables.

  Data Manipulation (SQL/Python)Onsite
• PinterestMedium·Data Scientist
  Write SQL to rank categories by impressions

  This question evaluates proficiency in SQL data manipulation—covering joins, aggregations, grouping, tie-breaking, date-window logic, and scalability considerations such as indexing and query performance—in the Data Manipulation (SQL/Python) domain.

  Data Manipulation (SQL/Python)Onsite
• PinterestMedium·Data Scientist
  Write windowed retention and ARPU SQL

  This question evaluates proficiency with SQL window functions, joins, aggregations and time-windowed analytics for computing retention and ARPU, as well as handling date truncation, UTC day boundaries and common data edge cases across user, session, and order tables.

  Data Manipulation (SQL/Python)Onsite
• PRPlymouth Rock Assurance CorporationMedium·Data Scientist
  Calculate Ultimate Loss by Policy Term

  This question evaluates a candidate's ability to perform sequence-aware cumulative aggregation and partitioned data manipulation, assessing competency in calculating running totals (ultimate loss) across policy-term records.

  Data Manipulation (SQL/Python)Technical Screen
• Point72Hard·Data Scientist
  Build the auction status table

  This problem tests advanced SQL skills, specifically the ability to perform window functions, handle state transitions, and aggregate time-series data to reconstruct the final status of entities.

  Data Manipulation (SQL/Python)Online AssessmentSQLWindow FunctionsData Aggregation
• Point72Medium·Data Scientist
  Convert Dates to Calendar Quarter Labels in SQL/Python

  This question evaluates a candidate's ability to perform date/time data transformation and normalization in SQL or Python, focusing on converting raw numeric dates into standardized quarter labels for aggregation and reporting.

  Data Manipulation (SQL/Python)Technical Screen
• Point72Medium·Data Scientist
  Write SQL for top student per department

  This question evaluates proficiency in SQL query formulation, including group-wise selection, joins, NULL handling, deterministic tie-breaking and ordering to identify a top-per-group student.

  Data Manipulation (SQL/Python)Technical Screen
• RedditMedium·Data Scientist
  Query US-based users and most active forums

  This question evaluates SQL data manipulation skills, including time-based filtering, joins, aggregations, null-safe handling, ratio computation, distinct counts, and top-N ranking to determine user residency and forum activity.

  Data Manipulation (SQL/Python)Technical Screen
• RobinhoodMedium·Data Scientist
  Create OHLC Aggregates from Tick Data in Python

  This question evaluates a candidate's ability to perform time-series bucketing and OHLC aggregation from tick data, testing skills in data parsing, stateful aggregation, and handling missing-interval forward-filling; it falls under Data Manipulation (SQL/Python) and assesses practical application rather than purely conceptual understanding.

  Data Manipulation (SQL/Python)Onsite
• RobinhoodMedium·Data Scientist
  Identify Top Users with Declined Transactions in SQL

  This question evaluates proficiency in SQL data manipulation, specifically aggregation, window functions, rolling 24-hour time-window analytics, NULL handling, and conditional classification via CASE WHEN within a fraud/risk detection scenario.

  Data Manipulation (SQL/Python)Technical Screen
• RobinhoodMedium·Data Scientist
  Identify Transactions During 'Golden' Membership Period

  This question evaluates proficiency in temporal data manipulation and aggregation, covering SQL date-range joins, window functions for per-user ranking, and Python frequency counting of senders and receivers, and it falls under the Data Manipulation (SQL/Python) domain for data scientist roles.

  Data Manipulation (SQL/Python)Technical Screen
• RobinhoodMedium·Data Scientist
  List Transactions During Active 'Gold' Membership Period

  This question evaluates proficiency in SQL-based data manipulation and temporal reasoning, specifically the ability to correlate membership periods with transaction records using relational operations.

  Data Manipulation (SQL/Python)Technical Screen
• RobinhoodMedium·Data Scientist
  Write SQL and Python for transaction analytics

  This question evaluates data manipulation competency in SQL and Python, covering normalization of transaction direction, JOINs and CASE logic, window functions for ranking and aggregation, and designing single-pass counting algorithms for streaming-like inputs.

  Data Manipulation (SQL/Python)Technical Screen
• RobinhoodMedium·Data Scientist
  Write SQL to localize trading drop contributors

  This question evaluates proficiency in SQL-based data manipulation and analytics, including cohorting by signup month, daily aggregation of executed trades per active user, segmentation by platform and geolocation, and competency with joins, timestamps, and operational flags.

  Data Manipulation (SQL/Python)Technical Screen
• RobloxMedium·Data Scientist
  Analyze Recent Orders Dataset with Python/pandas

  This question evaluates proficiency in data manipulation and aggregation using Python/pandas, including extracting per-user maximums, computing overall summary statistics, and producing daily aggregates from time-stamped records.

  Data Manipulation (SQL/Python)Onsite
• RobloxMedium·Data Scientist
  Compare ROW_NUMBER, RANK, and DENSE_RANK for Top-k Results

  Compare ROW_NUMBER, RANK, and DENSE_RANK with ties, exact-row limits, distinct score levels, and deterministic top-k semantics.

  Data Manipulation (SQL/Python)Technical Screen
• RobloxMedium·Data Scientist
  Compute ARPDAU/ARPPU by country

  This question evaluates data manipulation and analytics skills for computing user- and revenue-based metrics (ARPDAU, ARPPU), focusing on aggregation, multi-key joins, deduplication, time-window filtering, and correct revenue attribution.

  Data Manipulation (SQL/Python)Technical Screen
• RobloxMedium·Data Scientist
  Generate Friendship List with Acceptance Dates Using Pandas

  This question evaluates proficiency in data manipulation and relational reasoning using Python/pandas, focusing on transforming event logs into canonical pairwise relationships and extracting activation timestamps.

  Data Manipulation (SQL/Python)Onsite
• RobloxMedium·Data Scientist
  Match requests and accepts into friendships in SQL

  This question evaluates a candidate's competency in SQL data manipulation, focusing on temporal joins, deduplication of bidirectional relationships, selecting the earliest valid event, and reasoning about event-order constraints.

  Data Manipulation (SQL/Python)Onsite
• RobloxMedium·Data Scientist
  Write SQL for ads metrics and variability

  This question evaluates a candidate's ability to perform SQL-based data manipulation and analytics, including deduplication of events, computation of daily and campaign-level metrics (CTR, CPC), and calculation of statistical summaries (mean and standard deviation) and outlier detection over a specified date range.

  Data Manipulation (SQL/Python)Technical Screen
• RobloxEasy·Data Scientist
  Write SQL for influence score and follower growth

  This question evaluates SQL data manipulation competencies such as joins, aggregations, distinct counts, window functions, and time-based grouping for computing an influence score (engagements on a user's posts plus follower count) and monthly follower growth, and it falls under Data Manipulation (SQL/Python).

  Data Manipulation (SQL/Python)Technical Screen
• RobloxMedium·Data Scientist
  Write SQL to flag suspect payments and chargebacks

  This question evaluates proficiency with SQL conditional logic (CASE WHEN), JOINs, date/time arithmetic, aggregation, and encoding business rules for flagging suspect payments and chargebacks, and is categorized under Data Manipulation (SQL/Python) for a Data Scientist role.

  Data Manipulation (SQL/Python)HR Screen
• RRokuMedium·Data Scientist
  Write SQL for profit, growth, retention

  This question evaluates a candidate's ability to perform advanced SQL data manipulation — specifically rolling-window aggregations, revenue and gross profit computations that account for refunds, order status and test flags, plus cohort retention and week-over-week growth analysis.

  Data Manipulation (SQL/Python)Technical Screen