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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.
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Showing 6781–6810 of 9403 results
- PayPalEasyData ScientistHow to evaluate a new homepage feature
A PayPal data science technical screen on designing an A/B test to evaluate a new homepage feature. It covers experiment design and randomization, primary/secondary/guardrail metric selection with tradeoffs, sample-size and power estimation, and pitfalls like novelty effects and interference. The solution emphasizes value-aligned metrics (payment completion over CTR) and fraud guardrails specific to a payments product.
Analytics & ExperimentationTechnical Screen - PayPalMediumData ScientistHow to validate production models?
This question assesses the end-to-end strategy for validating a production-ready machine learning model, focusing on rigorous testing frameworks, drift detection, and business-risk mitigation.
Machine LearningOnsiteModel ValidationProduction MLFraud Detection - PayPalMediumData ScientistIdentify Session with Maximum Overlapping Sessions Count
This question evaluates temporal interval reasoning, set-based querying and aggregation skills, focusing on identifying and counting overlapping time intervals using SQL or equivalent Python data-manipulation tools.
Data Manipulation (SQL/Python)Onsite - PayPalMediumData ScientistIdentify Users with Specific Page Visit Sequence
This question evaluates event-sequence detection and temporal ordering skills in SQL, focusing on concepts such as windowing, adjacent-row reasoning, and session-scoped grouping to identify ordered page visits.
Data Manipulation (SQL/Python)Onsite - PayPalMediumData ScientistImplement sliding-window device anomaly
This question evaluates understanding of streaming algorithms, sliding-window state management, per-user data structures, and handling out-of-order events under strict time and space complexity constraints.
Coding & AlgorithmsTechnical Screen - PayPalMediumData ScientistInfluence Stakeholders Without Authority: Strategies and Examples
This interview question evaluates behavioral evidence, ownership, communication, trade-offs, and measurable outcomes in a realistic interview setting. A strong answer for Influence Stakeholders Without Authority: Strategies and Examples states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Behavioral & LeadershipOnsite - PayPalHardData ScientistInterpret p-values and common pitfalls
Evaluates interpretation of p-values, hypothesis testing, experimental design and statistical pitfalls in a fraud/experimentation context—including concepts like effect size, statistical power, multiple comparisons, delayed/rare outcomes, and imperfect randomization; category/domain: Statistics & Math.
Statistics & MathTechnical Screen - PayPalMediumData ScientistMaster A/B Testing: Key Concepts and Methodologies Explained
Evaluates practical A/B testing and causal inference fundamentals for online products. Strong answers cover p-values, errors, power, workflow, Simpson's paradox, metrics, and observational causal methods.
Analytics & ExperimentationOnsite - PayPalMediumMachine Learning EngineerMaximize ones with limited flips
This question evaluates proficiency with array algorithms, particularly sliding-window and two-pointer reasoning, complexity analysis, and the ability to adapt solutions for streaming data.
Coding & AlgorithmsOnsite - PayPalMediumSoftware EngineerMinimize a String Using Allowed Swaps
This question evaluates understanding of graph connectivity and constrained string reordering, along with proficiency in applying efficient data structures and algorithms for handling large inputs.
Coding & AlgorithmsOnsite - PayPalEasyData ScientistReduce airport ride cancellations under causal constraints
A PayPal Data Scientist onsite product-sense and causal-inference case: design a measurement framework, hypotheses, and experimentation strategy to reduce airport ride cancellations in a ride-hailing marketplace without harming marketplace health. It tests metric trees, interference-aware experiment design (switchback, partial-population, encouragement/IV), satisfaction proxies, confounder handling, and stakeholder communication.
Analytics & ExperimentationOnsite - PayPalMediumData ScientistResolve Conflicts in Data Science Leadership Scenarios
This interview question evaluates behavioral evidence, ownership, communication, trade-offs, and measurable outcomes in a realistic interview setting. A strong answer for Resolve Conflicts in Data Science Leadership Scenarios states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Behavioral & LeadershipOnsite - PayPalMediumMachine Learning EngineerSearch a word in a grid
This question evaluates proficiency in grid traversal and stateful search techniques such as depth-first search and backtracking, including visited-state management and pruning strategies within the Coding & Algorithms domain.
Coding & AlgorithmsOnsite - PayPalEasyData ScientistShould you play a dice payout game?
This question evaluates understanding of probability, expected value, and payoff-driven decision-making by requiring computation of expected return from discrete game outcomes. It is commonly asked to assess quantitative reasoning in the Statistics & Math category and primarily tests conceptual understanding of expected value and probabilistic reasoning rather than practical implementation.
Statistics & MathOnsite - PayPalMediumSoftware EngineerSolve common search/parse/graph frequency tasks
This problem tests your ability to perform a binary search on a rotated sorted array and subsequently count occurrences of elements to identify the top-k most frequent items.
Coding & AlgorithmsTechnical ScreenBinary SearchHash TableHeap - PayPalMediumData ScientistWrite SQL to flag Venmo ATO
This question evaluates a candidate's ability to construct complex SQL to detect account-takeover (ATO) signals in a payments platform, assessing skills in event-time windowing, deduplication, joins across user/login/transaction tables, and categorical flagging of new devices or IPs.
Data Manipulation (SQL/Python)Technical Screen - PayPalEasyData ScientistWrite SQL using HAVING and window functions
This question tests the ability to filter aggregated data using the HAVING clause and compute relative metrics using window functions to identify high-frequency transaction patterns.
Data Manipulation (SQL/Python)Technical ScreenSQLWindow FunctionsAggregations - PayPalMediumData ScientistWrite conditional aggregates with CASE WHEN
Write conditional aggregates with CASE WHEN evaluates SQL or pandas logic, joins, grouping, window functions, null handling, edge cases, and validation in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Data Manipulation (SQL/Python)Onsite - PayPalMediumData ScientistWrite conditional aggregation SQL queries
This question evaluates proficiency with conditional aggregation in SQL, including the use of SUM(CASE WHEN ...) versus filtering with WHERE and the implications of placing aggregation filters in HAVING for grouped queries, within the Data Manipulation (SQL/Python) domain.
Data Manipulation (SQL/Python)Onsite - PerceptyxMediumSoftware EngineerDemonstrate a Project and Defend Its Design
Tests your ability to present an end-to-end software project you built or led, defend key technical design decisions and trade-offs, and architect a forward-looking feature extension under live questioning.
Software Engineering FundamentalsTechnical ScreenSystem DesignArchitectureProject Walkthrough - PeregrineMediumSoftware EngineerFetch, group, and print paginated activities
This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Fetch, group, and print paginated activities states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Coding & AlgorithmsTechnical Screen - PermitflowMediumSoftware EngineerDistinguish Permit Requirement Outcomes
This problem tests your ability to model state transitions based on complex rule sets and implement efficient logic to resolve status precedence when multiple criteria are met.
Coding & AlgorithmsTechnical ScreenAlgorithmsLogicSet Theory - PerplexityMediumSoftware EngineerDesign a CreditTracker with expirations
This question evaluates a candidate's ability to design and implement data structures and algorithms for managing time-bound resources with non-monotonic (out-of-order) operations, emphasizing correctness and efficiency within the coding & algorithms domain.
Coding & AlgorithmsTechnical Screen - PerplexityHardSoftware EngineerDesign a personal finance aggregator
This question evaluates skills in large-scale system design including API and third-party integrations, data ingestion and normalization, transactional consistency and idempotency, security and privacy controls, data modeling for multi-currency financial records, and operational concerns like alerts and budgeting.
System DesignTechnical Screen - PerplexityMediumSoftware EngineerDesign personalized discovery recommendations
This problem evaluates your ability to design a scalable, real-time recommendation system that balances personalization with content discovery in an information-seeking environment.
ML System DesignOnsiteRecommender SystemsML InfrastructureRanking - PerplexityMediumSoftware EngineerDesign trending queries ranking system
This question tests the ability to design a high-throughput, real-time pipeline that identifies and ranks trending search queries, requiring trade-offs between freshness, accuracy, and system latency.
ML System DesignOnsiteSystem DesignReal-time StreamingRanking - PerplexityHardSoftware EngineerDiagnose overloaded Kubernetes cluster
This question evaluates competency in diagnosing and mitigating production overloads in Kubernetes-based microservice architectures, emphasizing observability, autoscaling behavior, resource constraints, and incident-response reasoning.
System DesignTechnical Screen - PerplexityMediumSoftware EngineerImplement Dependency-Aware To-Do List
Design an in-memory task management system that tracks directed dependencies between tasks, prevents cycles, and unblocks dependent tasks upon completion.
Coding & AlgorithmsTechnical ScreenGraphDesignTopological Sort - PerplexityMediumData ScientistImplement Stratified Sampling by Country
Implement proportional stratified sampling on an in-memory list of records partitioned by a categorical key, ensuring exact sample size via the largest remainder method and reproducible selection.
Coding & AlgorithmsTechnical Screenalgorithmsstatisticssampling - PerplexityHardSoftware EngineerImplement Task Dependencies and Failure
This question evaluates understanding of graph-based data structures and algorithms for modeling bidirectional task dependencies, status tracking, and efficient cascading failure propagation in an in-memory task manager.
Coding & AlgorithmsTechnical Screen
PayPal
Perplexity