Data Scientist Interview Questions

Showing 31–60 of 339 results

• AmazonMedium·Data Scientist
  Select Top Customers Using Transaction Data Filters

  This question evaluates a candidate's ability to perform data aggregation, filtering, ranking, and deterministic tie-breaking on transactional datasets, assessing skills in Data Manipulation (SQL/Python).

  Data Manipulation (SQL/Python)Technical Screen
• AmazonMedium·Data Scientist
  Transform event logs with subscription windows in pandas

  This question evaluates a candidate's competency in time-based event attribution and temporal interval manipulation using pandas, covering interval merging, subscription-aligned revenue aggregation, anomaly flagging, and handling edge cases like overlapping or back-to-back subscriptions.

  Data Manipulation (SQL/Python)Onsite
• AmazonMedium·Data Scientist
  Understand SQL: DELETE vs TRUNCATE, VIEW vs TABLE, CROSS JOIN

  This question evaluates a candidate's understanding of core SQL concepts and data-manipulation competencies, covering the behavior of data-deletion operations, distinctions between logical and physical data structures, and join semantics.

  Data Manipulation (SQL/Python)Technical Screen
• AmazonMedium·Data Scientist
  Verify subscriptions and analyze orders with SQL/Python

  This question evaluates proficiency in SQL and pandas data manipulation, covering data-quality validation, temporal sequence reasoning, deduplication, deterministic aggregation, and tie-breaking logic.

  Data Manipulation (SQL/Python)Technical Screen
• AppleEasy·Data Scientist
  Write queries to compute salary and budget stats

  This set of tasks evaluates data manipulation and analytical competencies, specifically the ability to compute order-statistics on numeric columns, perform relational joins to enrich event records, and reason about constrained selection for maximizing hires using SQL and pandas.

  Data Manipulation (SQL/Python)Onsite
• AtlassianMedium·Data Scientist
  Find 2023 NCAA championship winner

  This question evaluates proficiency in SQL data manipulation and relational reasoning, testing the ability to identify a championship winner from game result records across related tables in the Data Manipulation (SQL/Python) domain for data scientist roles.

  Data Manipulation (SQL/Python)Technical Screen
• B(Block (Square)Medium·Data Scientist
  Write left-join queries with tricky filters

  This question evaluates SQL data-manipulation skills including LEFT JOIN semantics, aggregation functions like COUNT(DISTINCT) and SUM, GROUP BY/HAVING logic, and date-window filtering for referral and order analytics.

  Data Manipulation (SQL/Python)Technical Screen
• Boston Consulting GroupMedium·Data Scientist
  Manipulate and merge DataFrames correctly

  This question evaluates proficiency in pandas-based data manipulation and merging, covering join validation, vectorized revenue and discount calculations, missing-value imputation, groupby/transform usage, dtype setting, and avoiding SettingWithCopy issues.

  Data Manipulation (SQL/Python)Technical Screen
• Boston Consulting GroupMedium·Data Scientist
  Merge and Clean Customer Order Data for Analysis

  This question evaluates proficiency in data manipulation with pandas and SQL concepts, focusing on dataset merging, missing-value handling, and computing derived aggregate columns such as total_spent.

  Data Manipulation (SQL/Python)Online Assessment
• Boston Consulting GroupMedium·Data Scientist
  Merge and Concatenate Inconsistent Order Files with Pandas

  This question evaluates proficiency with pandas-based data manipulation, including schema alignment, column renaming, type casting, and vertical concatenation when merging CSV files.

  Data Manipulation (SQL/Python)Online Assessment
• Boston Consulting GroupMedium·Data Scientist
  Query top spenders and 7-day growth

  This question evaluates proficiency in SQL data manipulation, including aggregations, date-range filtering, joins, window functions for ranking and tie-breaking, and computing revenue shares and growth rates within a relational schema.

  Data Manipulation (SQL/Python)Technical Screen
• Boston Consulting GroupMedium·Data Scientist
  Transform messy transactions with pandas

  This question evaluates proficiency in large-scale data manipulation and feature engineering using pandas, covering timestamp normalization across time zones, deduplication and last-write-wins semantics, data validation, memory-efficient aggregation, rolling-window statistics, and top-k categorical extraction for merchant categories.

  Data Manipulation (SQL/Python)Technical Screen
• Boston Consulting GroupMedium·Data Scientist
  Visualize and Clean SKU Sales Data for Outliers

  This question evaluates data manipulation and exploratory data analysis skills, including aggregation, outlier detection (IQR/Z-score) and visualization using Python libraries such as pandas and matplotlib/seaborn.

  Data Manipulation (SQL/Python)Technical Screen
• BByteDanceMedium·Data Scientist
  Campaign Efficiency Metrics and Below-Average CTR

  Practice a data scientist SQL interview question that calculates campaign cost and funnel rates, handles zero denominators, and filters campaigns against an average CTR benchmark. The exercise tests PostgreSQL date arithmetic, CTE organization, NULL-safe calculations, and deterministic output.

  Data Manipulation (SQL/Python)Technical Screen
• BByteDanceMedium·Data Scientist
  Compare SQL counts, windows, and NULL semantics

  This question evaluates understanding of SQL aggregation and NULL semantics, window functions (ROW_NUMBER vs RANK), join behavior to avoid double-counting, and defensive handling of NULLs and divide-by-zero using COALESCE and NULLIF in a data manipulation context.

  Data Manipulation (SQL/Python)Technical Screen
• BByteDanceMedium·Data Scientist
  Find Each User's Earliest Seven-Day Activity Streak

  Tests your ability to identify consecutive date sequences (gaps-and-islands problem) in PostgreSQL, aggregate streaks, and filter for each user's earliest qualifying period.

  Data Manipulation (SQL/Python)Technical Screensqlpostgresqlwindow-functions
• BByteDanceMedium·Data Scientist
  Find top-paid employee per department

  This problem tests your ability to perform group-wise filtering and ranking using window functions or joins to extract top-performing records within categories.

  Data Manipulation (SQL/Python)Technical ScreenSQLWindow FunctionsAggregation
• CVS HealthMedium·Data Scientist
  Aggregate radiology spend and derive fiscal month

  This question evaluates a candidate's competency in data manipulation and preprocessing using SQL/Python, covering robust dtype specification, null handling, numeric aggregation and percentage computation, datetime parsing, and fiscal-month derivation.

  Data Manipulation (SQL/Python)Technical Screen
• CVS HealthMedium·Data Scientist
  Calculate annual percentages and YoY by cohorts

  This question evaluates SQL and pandas data manipulation skills, specifically joins, conditional aggregation, deduplication, cohort-based percentage computations, and year-over-year change calculations.

  Data Manipulation (SQL/Python)Technical Screen
• CVS HealthEasy·Data Scientist
  Compute specialty spend share and top age band

  This question evaluates data manipulation and aggregation skills in SQL and Pandas, including joins/unions across disjoint member tables, computation of specialty spend shares, identification of top age bands by claim counts with tie handling, year-based date filtering, and categorical recoding with monthly grouping.

  Data Manipulation (SQL/Python)Technical Screen
• CVS HealthMedium·Data Scientist
  Create Views, Insert, and Update Correctly

  This question evaluates SQL data-manipulation competencies including view creation, aggregate joins, INSERT/UPDATE operations, and reasoning about temporal effects on computed aggregates such as historical customer spend.

  Data Manipulation (SQL/Python)Online Assessment
• CVS HealthMedium·Data Scientist
  Create and query an e-commerce schema

  This question evaluates SQL schema design and data manipulation competencies, including defining PostgreSQL table types and constraints, inserting exact datasets, composing aggregate and join queries with date-based filters, and performing DML updates with verification.

  Data Manipulation (SQL/Python)Online Assessment
• CVS HealthMedium·Data Scientist
  Use pandas to aggregate, pivot, and label

  This question evaluates competency in pandas-based tabular data manipulation—specifically DataFrame merging, groupby aggregation, pivot table construction, counting unique values, and conditional flagging with numpy—within the domain of Data Manipulation (SQL/Python) and is primarily at the practical application level.

  Data Manipulation (SQL/Python)Technical Screen
• CVS HealthMedium·Data Scientist
  Write SQL for dedup and purchase shares

  This question evaluates proficiency in SQL data manipulation skills including entity deduplication, canonicalization rules, window functions, common table expressions, joins, and aggregation to derive per-user purchase counts and distributions.

  Data Manipulation (SQL/Python)Technical Screen
• Capital OneMedium·Data Scientist
  Aggregate exam scores with NULL handling

  This question evaluates proficiency in SQL data manipulation, specifically joins (including LEFT JOIN behavior), NULL handling with ISNULL/COALESCE, conditional aggregation, distinct counts, and date-based filtering within the Data Manipulation (SQL/Python) domain, focusing on practical application of query-writing skills.

  Data Manipulation (SQL/Python)Online Assessment
• Capital OneMedium·Data Scientist
  Audit flight data quality from metadata

  This question evaluates data quality auditing competencies, including validation of timestamps and timezones, detection of label leakage and inconsistent units, provenance and schema enforcement, and hands‑on use of SQL/Python for dataset inspection.

  Data Manipulation (SQL/Python)Onsite
• Capital OneMedium·Data Scientist
  Calculate Longest Transaction Streak for Each User

  This question evaluates proficiency in data manipulation and time-series sequence analysis, specifically measuring the longest run of consecutive successful transactions per user from transactional logs.

  Data Manipulation (SQL/Python)Technical Screen
• Capital OneEasy·Data Scientist
  Clean and Merge Housing Data

  This question tests the ability to clean messy housing datasets, handle inconsistent data types, and perform efficient left-joins with external reference data.

  Data Manipulation (SQL/Python)OnsitePandasData CleaningSQL
• Capital OneMedium·Data Scientist
  Compute Customer Spend and Engineer Features for 2023

  This question evaluates proficiency in SQL-based temporal aggregation and Python feature engineering on transactional datasets, including computing monthly spend summaries and engineering category-level spending features.

  Data Manipulation (SQL/Python)Onsite
• Capital OneMedium·Data Scientist
  Determine Country with Most 'Sunny' Days

  This question evaluates proficiency in data aggregation, grouping, and filtering to summarize categorical time-series records using SQL or equivalent Python data-manipulation tools, and it belongs to the Data Manipulation domain with an emphasis on practical application of query and aggregation techniques.

  Data Manipulation (SQL/Python)Onsite