Interview Questions

Showing 5401–5430 of 9403 results

• MetaMedium·Data Scientist
  Write SQL for Pixel Signal Metrics

  This question evaluates SQL-based data manipulation and analytical competencies, specifically joining and aggregating event and ad performance tables, computing event-weighted metrics and composite data-quality scores (such as validity and match-rate based measures) across a 30-day window.

  Data Manipulation (SQL/Python)Technical Screen
• MetaEasy·Product Analyst
  Write SQL for call pickup and usage metrics

  This question tests the ability to join event logs, filter by session timing, and calculate per-user metrics using window functions or group-by operations.

  Data Manipulation (SQL/Python)OnsiteSQLAggregationJoins
• MetaHard·Data Engineer
  Write SQL for car rental utilization by city

  This question evaluates proficiency in SQL querying and relational data modeling, focusing on time-interval overlap logic, distinct aggregation across joined tables, null handling, and safe computation of utilization metrics.

  Coding & AlgorithmsOnsite
• MetaMedium·Data Scientist
  Write SQL for comment analytics

  This question evaluates proficiency in SQL analytics, specifically joins, filtering, aggregation (distinct counts), percentile functions, time-windowed grouping, handling soft-deleted records, and writing efficient queries via CTEs.

  Data Manipulation (SQL/Python)Onsite
• MetaMedium·Data Scientist
  Write SQL for daily chats and fast replies

  This question evaluates a candidate's ability to manipulate relational data and reason about temporal event sequences, specifically testing skills in SQL aggregation, distinct counting, deduplication, bidirectional relationship handling, and time-windowed event matching.

  Data Manipulation (SQL/Python)Technical Screen
• MetaMedium·Data Engineer
  Write SQL for library analytics

  This question evaluates proficiency in SQL-based data manipulation and analytical querying, focusing on relational schema navigation, joins, aggregation, filtering, and handling temporal and conditional metrics within a library dataset.

  Data Manipulation (SQL/Python)Technical Screen
• MetaMedium·Data Scientist
  Write SQL for multi-account metrics

  This question tests your ability to perform complex aggregations across multiple tables, specifically using conditional logic and joins to compute user engagement metrics.

  Data Manipulation (SQL/Python)Technical ScreenSQLAggregationJoins
• MetaMedium·Data Scientist
  Write SQL for retention, conversion, and churn

  This question evaluates proficiency in SQL-based analytics and time-aware data manipulation, covering cohort and retention computation, conversion and churn metrics, user-level deduplication across platforms, timezone-local day handling, rolling-window comparisons, and calculation of statistical confidence intervals.

  Data Manipulation (SQL/Python)Onsite
• MetaMedium·Data Scientist
  Write SQL for seller and category metrics

  This question tests the ability to perform complex aggregations, handle date filtering, and calculate performance ratios while managing potential division-by-zero errors in a multi-table SQL environment.

  Data Manipulation (SQL/Python)Technical ScreenSQLAggregationJoins
• MetaMedium·Data Scientist
  Write SQL for social feed metrics and ties

  This question evaluates advanced SQL analytics skills and competency in data modeling for social feed metrics, including relationship joins, viewer-day temporal aggregation, weighted interaction scoring, and per-user top-N ranking.

  Data Manipulation (SQL/Python)Technical Screen
• MetaMedium·Data Scientist
  Write SQL to analyze shop visibility

  This question evaluates proficiency in SQL-based time-series and event-data manipulation, including deduplication of consecutive states, window functions, aggregation, cohort analysis, and percentile/summary statistics.

  Data Manipulation (SQL/Python)Onsite
• MetaMedium·Data Scientist
  Write SQL to compare exclusive category engagement

  This question evaluates SQL-based data manipulation and cohort analysis competencies, including cohort definition, session-level filtering and aggregation for metrics such as user counts, median active days, proportions, and per-user average minutes while applying data-quality constraints over a fixed date window.

  Data Manipulation (SQL/Python)Onsite
• MetaMedium·Data Scientist
  Write SQL to flag coordinated fake accounts

  This question evaluates proficiency in SQL-based data manipulation, temporal windowing, event-table joins, aggregation and feature engineering for fraud detection, including computing weighted risk_score flags across user activity.

  Data Manipulation (SQL/Python)Onsite
• MetaMedium·Data Scientist
  Write SQL to infer group-call demand

  This question evaluates SQL-based data manipulation and product-analytics competencies, including temporal sessionization, graph connectivity inference for detecting overlapping 1:1 call loops, deduplication trade-offs (UNION vs UNION ALL), and computation of derived metrics to estimate latent feature demand within the Data Manipulation (SQL/Python) domain. It is commonly asked because it measures practical application of event-time windowing, connected-component reasoning and edge-case handling (e.g., excluding failed connections) for producing daily summary metrics, emphasizing hands-on SQL proficiency over purely conceptual understanding.

  Data Manipulation (SQL/Python)Technical Screen
• MetaMedium·Data Scientist
  Write SQL/pandas for KPI anomaly

  This question evaluates proficiency with SQL window functions and equivalent pandas operations for KPI anomaly detection, covering baseline computation using same-weekday medians over eight weeks, per-country and per-post_type Likes-per-DAU metrics with deduplication of users for DAU, outage filtering, attribution of declines between new and existing users, and time-series comparisons like friend-request acceptance rates while explicitly handling duplicates, sparse or missing DAU rows, and timezone issues. It is commonly asked in Data Manipulation (SQL/Python) interviews to assess practical data engineering and analytical skills, primarily testing practical application with an underlying need for conceptual understanding of baselining, attribution, and data-quality edge cases.

  Data Manipulation (SQL/Python)Onsite
• MetaMedium·Data Scientist
  Write advanced SQL for sales support analytics

  This question evaluates practical SQL data-manipulation skills such as joins, aggregation, window functions, time-based filtering, deduplication, and computation of sales KPIs for rep-level analytics.

  Data Manipulation (SQL/Python)Technical Screen
• MetaMedium·Data Scientist
  Write dating profile report with final reviews

  This question evaluates SQL and data-manipulation proficiency, including temporal joins, versioning, time-bounded snapshotting, windowed aggregations, and validation checks for data quality and idempotency.

  Data Manipulation (SQL/Python)Onsite
• MetaMedium·Data Engineer
  Write queries for follows and bookings

  This problem tests your ability to manage relational data, handle temporal overlaps for booking availability, and derive insights from social graph-like connections using SQL or data manipulation scripts.

  Coding & AlgorithmsTechnical ScreenSQLIntervalsGraphs
• MetaMedium·Data Scientist
  [Analytical Reasoning] Comparing Two Newsfeed Ad Insertion Methods

  Compare independent versus blocked ad insertion in a 100-post feed. Includes expected ads, tail risk, consecutive ad probabilities, longest streaks, product tradeoffs, and A/B test design.

  Analytics & ExperimentationOnsite
• MMetropolisMedium·Software Engineer
  Deep-dive a cross-team technical project you led

  This question evaluates leadership, cross-team collaboration, technical ownership, project management, and the ability to make architecture trade-offs, mitigate reliability/security/performance risks, and quantify outcomes.

  Behavioral & LeadershipTechnical Screen
• MMetropolisMedium·Software Engineer
  Describe disagreement with leadership and your approach

  This question evaluates interpersonal competencies such as conflict resolution, communication, stakeholder management and leadership judgment within a software engineering context.

  Behavioral & LeadershipTechnical Screen
• MMetropolisMedium·Software Engineer
  Explain how you use AI tools in development

  This question evaluates a developer's familiarity with AI-assisted development tools, practical experience integrating them into workflows, and understanding of associated governance, security, and data-handling concerns.

  Software Engineering FundamentalsTechnical Screen
• MMetropolisMedium·Software Engineer
  Introduce yourself and explain your job search goals

  This question evaluates communication, self-presentation, articulation of career goals, alignment with role expectations, and the ability to address logistical constraints for a senior software engineering position.

  Behavioral & LeadershipTechnical Screen
• MMicro1Medium·Software Engineer
  Compare Promise.all, Promise.any, and Promise.allSettled

  Analyze and compare the behavior of JavaScript's `Promise.all`, `Promise.any`, and `Promise.allSettled` across resolution semantics, failure handling, result ordering, and empty inputs, then apply them to real-world distributed service orchestration.

  Software Engineering FundamentalsOnline Assessmentjavascriptpromisesconcurrency
• MMicro1Medium·Software Engineer
  Merge Overlapping Intervals

  Tests sorting and linear scanning techniques to consolidate overlapping and adjacent closed intervals into a minimal sorted set.

  Coding & AlgorithmsOnline Assessmentarrayssortingintervals
• MicrosoftMedium·Software Engineer
  Adapt When Project Requirements Change Midway

  Explain a mid-project requirement change through concrete first steps, personal ownership, alternatives, scope trade-offs, and revised acceptance criteria.

  Behavioral & LeadershipOnsite
• MicrosoftMedium·Software Engineer
  Answer Running Median Queries Over a Stream of Inserted Integers

  A coding problem that processes a stream of add and median operations and returns, for every query, the median of all integers inserted so far. It tests choosing data structures that keep the middle of a growing collection quickly accessible, plus correct averaging when the count is even.

  Coding & AlgorithmsOnsite
• MicrosoftMedium·Software Engineer
  Answer common graph, grid, and array tasks

  This problem tests your ability to model a dependency system as a directed graph and identify if a valid order exists using cycle detection (Kahn's Algorithm or DFS).

  Coding & AlgorithmsTechnical ScreenGraphTopological SortDFS
• MicrosoftHard·Software Engineer
  Answer suffix maximum-frequency queries

  This problem tests your ability to optimize range frequency queries using precomputation and efficient data structures, specifically focusing on suffix-based constraints.

  Coding & AlgorithmsOnsiteBinary SearchData StructuresArrays
• MicrosoftMedium·Software Engineer
  Assemble DNA payload strings from tagged fragments

  This question evaluates proficiency in string manipulation, sequence assembly, and labeled-graph path reconstruction—skills involved in ordering fragments by matching start/end tags and concatenating payloads—and it belongs to the Coding & Algorithms domain.

  Coding & AlgorithmsTechnical Screen