Pinterest interview questions

Showing 1–30 of 161 results

• AI-Assisted Coding: Add a Read-Through Cache for a Product GET API in an Existing RepoHard

  In an AI-assisted coding round, add a read-through cache to an existing service so a product GET API calls ProductRepository less often, then explain the approach. It tests understanding a codebase before prompting, cache placement, expiry, invalidation and concurrency, and proving the change works.

  PinterestSoftware EngineerSoftware Engineering FundamentalsOnsite
• Analyze Global Engagement and Impressions with SQL QueriesMedium

  This question evaluates proficiency in SQL-based data manipulation and analytical querying, covering aggregation, grouping, ranking, and the correlation of impressions with user engagement and feature usage metrics.

  PinterestData ScientistData Manipulation (SQL/Python)Onsite
• Analyze a geo rollout and interpret chartsHard

  This question evaluates causal inference and product analytics competencies — specifically specification of causal estimands and difference-in-differences, segmented (interrupted) time-series regression, power and duration calculations, spillover and donor-pool diagnostics, and selection of guardrail metrics.

  PinterestData ScientistAnalytics & ExperimentationOnsite
• Analyze survey with gender imbalanceHard

  Analyze survey with gender imbalance evaluates statistical assumptions, formulas, estimation strategy, uncertainty, edge cases, and interpretation in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  PinterestData ScientistStatistics & MathOnsite
• Answer Policy Violation Log QueriesMedium

  Design an in-memory query engine over a timestamp-sorted policy violation log to support aggregate, point, and range queries efficiently using hash maps and binary search.

  PinterestSoftware EngineerCoding & AlgorithmsTechnical Screen
• Answer core ML fundamentals questionsHard

  This question evaluates a candidate's mastery of core Machine Learning fundamentals, including classification metrics (precision and recall) with confusion-matrix interpretation, gradient concepts for optimization, ensemble learning tradeoffs, and the mechanics of a neural network forward pass.

  PinterestMachine Learning EngineerMachine LearningOnline Assessment
• Assign Pins to Shortest ColumnsMedium

  This question evaluates understanding of greedy assignment strategies and data structures for maintaining and updating minimums in an online allocation problem, while also testing load-balancing reasoning and analysis of time and space complexity.

  PinterestSoftware EngineerCoding & AlgorithmsTechnical Screen
• Behavioral Deep Dive: Owned Project Metrics, Fast Decisions, Feedback, and ConflictHard

  Tests an engineering candidate's end-to-end technical leadership, ownership mindset, quantitative impact tracking, decision-making velocity under uncertainty, and interpersonal maturity.

  PinterestSoftware EngineerBehavioral & LeadershipOnsite
• Behavioral Round: Success Metrics, Slow Teammates, Team Health, Feedback and ConflictHard

  Prepare concise answers for a software engineer behavioral round covering how you defined a project's success metrics, leading and communicating with engineers, a slow teammate, good and poor teams, giving and receiving negative feedback, conflict, and your strongest quality. It tests specific, well-structured stories with clear ownership and measurable outcomes.

  PinterestSoftware EngineerBehavioral & LeadershipOnsite
• Bias-Variance Tradeoff and Vanishing Gradients in Feedforward NetworksHard

  Tests theoretical and mathematical understanding of the bias-variance decomposition and the vanishing-gradient phenomenon during backpropagation in deep feedforward architectures.

  PinterestMachine Learning EngineerMachine LearningTechnical Screen
• Build an emoji blaster animation on iOSMedium

  This question evaluates a developer's skills in iOS UI interaction, animation frameworks, event scheduling and concurrency, performance optimization, and designing testable application architecture.

  PinterestSoftware EngineerSoftware Engineering FundamentalsOnsite
• Calculate 95% Bootstrap Confidence Interval for Order ValuesMedium

  This question evaluates a data scientist's competence in statistical inference using bootstrap resampling, proficiency with numerical computing for large sample operations, and attention to performance optimization.

  PinterestData ScientistCoding & AlgorithmsOnsite
• Calculate the Percentage of Highly Active Users by CountryMedium

  Calculate highly active users by country over seven calendar days using distinct active dates and same-day surface diversity, with percentage output.

  PinterestData ScientistData Manipulation (SQL/Python)Technical Screen
• Clean and Aggregate Transactions for Finance DashboardMedium

  This question evaluates data cleaning and transformation competencies including pandas-based vectorized operations, categorical mapping and feature flagging, as well as aggregation and summarization of transactional data in the data manipulation (SQL/Python) domain.

  PinterestData ScientistData Manipulation (SQL/Python)Onsite
• Collect Pins from Reachable BoardsMedium

  Implement a breadth-first graph traversal over a collection of boards to collect unique pins in discovery order, handling cycles, shared children, and invalid references.

  PinterestSoftware EngineerCoding & AlgorithmsOnline Assessment
• Compute CTR by format for new US usersMedium

  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).

  PinterestData ScientistData Manipulation (SQL/Python)Technical Screen
• Compute average unique pins per userEasy

  This question evaluates a candidate's ability to process collections and compute aggregated metrics, including per-user deduplication of items, handling of missing/null entries, numeric averaging and rounding.

  PinterestData ScientistCoding & AlgorithmsTechnical Screen
• Compute percent of first-cancel users who never returnEasy

  This question evaluates a candidate's competency in data manipulation and temporal analysis using SQL/Python, focusing on computing user-level metrics and correctly ordering time-based events.

  PinterestData AnalystData Manipulation (SQL/Python)Technical Screen
• Compute percent of first-cancelled users who never rebookMedium

  This question evaluates proficiency in SQL data manipulation—specifically use of window functions, CTEs, deduplication by earliest timestamp, temporal comparisons, and cohort-level aggregation—within the Data Manipulation (SQL/Python) domain for a Data Analyst role in health‑tech product analytics.

  PinterestData AnalystData Manipulation (SQL/Python)Technical Screen
• Compute reachable cells for a cleaning robotMedium

  This problem tests graph traversal techniques (BFS/DFS) on a 2D grid, focusing on efficient coordinate management and state representation when navigating obstacles.

  PinterestSoftware EngineerCoding & AlgorithmsOnsite
• Connect Probability, Experiment Sizing, and Bootstrap InferenceHard

  Tests end-to-end statistical rigor across discrete probability modeling, sample size derivation for A/B testing, bootstrap confidence intervals for heavy-tailed engagement metrics, and translating conflicting inferential signals into product launch recommendations.

  PinterestData ScientistStatistics & MathOnsite
• Count Distinct Active Pins per Time Segment from Overlapping Interaction LogsHard

  Process overlapping pin interaction logs to calculate the number of distinct active pins over continuous time segments. Tests interval merging, line sweep techniques, and boundary handling.

  PinterestSoftware EngineerCoding & AlgorithmsOnsite
• Cross-reference logs to flag spam numbersMedium

  This question evaluates proficiency with data structures (such as hash maps), parsing and deduplication, frequency counting, input validation, and analysis of time and space complexity.

  PinterestSoftware EngineerCoding & AlgorithmsOnsite
• Decide if ad load is optimizedHard

  This question evaluates competency in analytics and experimentation, covering experiment design, metric and guardrail definition, causal inference, statistical testing, segmentation for heterogeneous effects, and balancing user experience versus monetization.

  PinterestData ScientistAnalytics & ExperimentationOnsite
• Decide target via subsequence plus/multiply expressionMedium

  A Pinterest software-engineer coding screen: given positive 32-bit integers and a target, decide whether some subsequence with '+'/'*' operators evaluated strictly left to right (equal precedence) hits the target, and return a valid expression. The answer spans forward backtracking, monotonicity-based pruning, a divisibility-guided reverse search from the target, complexity analysis, and 32-bit overflow handling.

  PinterestSoftware EngineerCoding & AlgorithmsTechnical Screen
• Decode and Explain Ambiguity in Compression StringsMedium

  This question evaluates parsing of compact count-value encodings, reasoning about ambiguous encodings, and combinatorial enumeration of all valid decodings.

  PinterestData ScientistCoding & AlgorithmsOnsite
• Deep-Dive Two Projects Through Technical DecisionsMedium

  This question tests your ability to articulate technical depth, decision-making frameworks, and engineering maturity by comparing two complex projects under different constraints.

  PinterestSoftware EngineerBehavioral & LeadershipOnsite
• Delete and Compact a Forest Stored by Parent IndicesMedium

  Implement subtree deletion on a parent-pointer forest array, supporting tombstoning and index compaction with pointer remapping.

  PinterestSoftware EngineerCoding & AlgorithmsTechnical Screen
• Demonstrate leadership with concrete STAR examplesHard

  This question evaluates leadership, stakeholder influence, metric-driven decision-making, ambiguity management, end-to-end analytical ownership, and resilience in a Data Scientist context, categorized under Behavioral & Leadership.

  PinterestData ScientistBehavioral & LeadershipOnsite
• Describe a Failure or Mistake and Its Lasting LessonMedium

  This question assesses your ability to reflect on professional shortcomings, demonstrate accountability, and translate failure into actionable growth for both yourself and your team.

  PinterestMachine Learning EngineerBehavioral & LeadershipOnsite