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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 2431–2460 of 3640 results
- NetflixEasyMachine Learning EngineerDesign an ML Platform Portal
This question assesses the ability to design an internal ML Platform Portal that streamlines the model lifecycle, focusing on experiment tracking, model registry, and workflow automation.
ML System DesignOnsiteMLOpsSystem DesignScalability - NetflixHardSoftware EngineerDesign an ad frequency capping system
This question evaluates competency in distributed systems architecture, real-time stateful services, high-cardinality time-series data modeling, API design for low-latency decision paths, and operational monitoring including consistency and latency trade-offs.
System DesignOnsite - NetflixMediumSoftware EngineerDesign an ads data model
This problem tests your ability to design a scalable, reliable data schema for an advertising platform that must support high-throughput event ingestion and real-time analytical queries.
System DesignOnsiteData ModelingScalabilityOLTP vs OLAP - NetflixHardData EngineerDesign config rollout and click aggregation
This problem tests your ability to design a global configuration distribution system combined with a high-throughput event processing pipeline to monitor rollout health.
System DesignOnsiteDistributed SystemsReal-time AnalyticsEvent Streaming - NetflixMediumData ScientistDetermine Maximum Consecutive Order Days Per User
Determine Maximum Consecutive Order Days Per User 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 - NetflixMediumData ScientistEstimate ATE of personalization on streaming
This question evaluates causal inference and experimental-analysis competencies by asking for estimation of the average treatment effect (ATE) of personalization on minutes streamed, reporting a 95% confidence interval, and reasoning about the use of pre-treatment covariates, and it sits in the Analytics & Experimentation domain for a Data Scientist role. It is commonly asked to assess application of randomized experiment analysis and statistical inference while probing conceptual understanding of causal assumptions and covariate adjustment, testing both conceptual understanding and practical application.
Analytics & ExperimentationOnsite - NetflixEasyData ScientistEstimate ATE, ITT, and TOT from experiment
This question tests the ability to distinguish and calculate Average Treatment Effect (ATE), Intent-to-Treat (ITT), and Treatment-on-the-Treated (TOT) in the presence of non-compliance.
Analytics & ExperimentationOnsiteCausal InferenceExperimentationInstrumental Variables - NetflixHardData EngineerExplain concurrency and reliability tradeoffs
This problem tests your understanding of balancing thread-safe resource management in a high-concurrency local environment against the systemic requirements of a distributed data pipeline.
Software Engineering FundamentalsOnsiteConcurrencyDistributed SystemsCaching - NetflixHardSoftware EngineerHow do you give and receive feedback?
This question evaluates a software engineer's interpersonal competencies, specifically the ability to give and receive constructive feedback, demonstrate emotional intelligence, take ownership, and collaborate across cross-functional teams.
Behavioral & LeadershipOnsite - NetflixMediumData ScientistHow to Design Effective A/B Tests for Onboarding
Evaluates A/B test design for a redesigned onboarding flow in a subscription app. Strong answers define activation, user-level randomization, primary and guardrail metrics, sample size, sequential monitoring, and decisions when activation improves but support burden rises.
Analytics & ExperimentationOnsite - NetflixEasyMachine Learning EngineerHow would you support ML stakeholders?
This question evaluates skills in ML infrastructure, stakeholder management, production monitoring, model iteration optimization, and data governance when collaborating with data science partners.
Behavioral & LeadershipOnsite - NetflixMediumData ScientistIdentify Longest Consecutive Incrementing Watch-Time Sequence
This question evaluates a candidate's ability to design and analyze efficient algorithms for detecting longest consecutive incrementing sequences in unsorted integer arrays, testing understanding of appropriate data structures and time/space complexity trade-offs.
Coding & AlgorithmsOnsite - NetflixMediumSoftware EngineerImplement Cache, Undo, and DFS
This problem tests your ability to combine a Least Recently Used (LRU) cache with a command-based undo system, applied to a hierarchical tree structure traversal.
Coding & AlgorithmsOnsiteLRU CacheDFSUndo Pattern - NetflixMediumSoftware EngineerImplement Caches, Undo, and Traversal
This question evaluates proficiency with data structures, API design, and system-level concerns by combining timed in-memory caching, command undo/redo semantics, and depth-first traversal of a tree; it falls under the Coding & Algorithms domain and is commonly asked to assess practical implementation skills, correctness under edge cases, and the ability to reason about time and space complexity. The level of abstraction spans practical application—designing clean APIs and implementing core logic—while also requiring conceptual understanding of complexity analysis and background cleanup or state-management patterns.
Coding & AlgorithmsOnsite - NetflixMediumSoftware EngineerImplement TTL Cache and Tree Balance Reporting
This question evaluates proficiency in designing efficient in-memory data structures and tree algorithms, specifically time-to-live cache behavior (expiration semantics and accurate unexpired counts) and per-node subtree-height computations for balance reporting, and it falls under the Coding & Algorithms domain.
Coding & AlgorithmsOnsite - NetflixHardSoftware EngineerImplement a Versioned Key-Value Store
This question evaluates understanding of time-versioned data storage, related data-structure selection, handling of overwrite semantics at equal timestamps, and the ability to reason about correctness and complexity trade-offs.
Coding & AlgorithmsOnsite - NetflixMediumData ScientistImplement longest increasing subarray with one deletion
This question evaluates proficiency in array algorithms and algorithmic optimization, focusing on handling boundary cases, reconstructing index ranges, and meeting strict O(n) time and O(1) extra-space constraints.
Coding & AlgorithmsOnsite - NetflixMediumSoftware EngineerImplement ordering and undo executor
This question evaluates graph algorithm skills (topological ordering and cycle detection) and software design competencies related to command interfaces, undo semantics, and shared-state management.
Coding & AlgorithmsOnsite - NetflixHardData EngineerImplement phrase search and JSON path
This problem tests your ability to process unstructured text into a searchable index and navigate hierarchical data structures using path patterns.
Coding & AlgorithmsOnsiteInverted IndexString ProcessingRecursion - NetflixMediumSoftware EngineerModel Direct-Sold DSP Orders
This Software Engineering Fundamentals question evaluates data and domain modeling skills for ad-technology order management, focusing on entities such as advertisers, agencies, orders, line items, targeting, creatives, delivery constraints, tracking events, reporting needs, and configuration versioning.
Software Engineering FundamentalsOnsite - NetflixMediumSoftware EngineerModel ads demand data for reporting
This question tests the ability to design a robust data pipeline and schema for tracking ad performance metrics, focusing on handling event-level data, aggregations, and dimension consistency.
System DesignOnsiteData EngineeringData ModelingETL - NetflixMediumSoftware EngineerModel data for an ads platform
This question evaluates proficiency in data modeling and database schema design for advertising systems, including entity-relationship modeling, privacy-aware user identifier handling, and delivery/tracking log representation.
System DesignOnsite - NetflixMediumData ScientistNavigate conflicting signals and ambiguous expectations
This question evaluates a Data Scientist's behavioral and leadership competencies — including adaptability to changing expectations, stakeholder management, prioritization between depth and breadth, decision-making principles, and post-outcome learning — and sits squarely in the Behavioral & Leadership domain.
Behavioral & LeadershipOnsite - NetflixMediumSoftware EngineerReason About a Movie Billboard Rotation Component
This problem tests the ability to manage dynamic scheduling and priority updates using balanced binary search trees (ordered maps) while handling concurrency and system scalability.
Software Engineering FundamentalsOnsiteData StructuresConcurrencySystem Design - NetflixMediumSoftware EngineerReport Tree Levels and Balanced Subtrees
Tests traversing a binary tree stored in array (heap) layout to compute subtree heights and identify nodes rooted at height-balanced subtrees along with their tree levels.
Coding & AlgorithmsOnsitebinary-treeheapdepth-first-search - NetflixMediumSoftware EngineerReturn valid task order from prerequisites
This question evaluates proficiency in graph algorithms, notably topological sorting and cycle detection, as well as algorithmic complexity analysis and handling of dependency constraints.
Coding & AlgorithmsOnsite - NetflixMediumSoftware EngineerShow role fit using past ad experience
This question evaluates a candidate's ability to demonstrate role fit by mapping past ads engineering projects to job requirements and communicating measurable impact, assessing competencies such as ownership, cross-functional collaboration, incident debugging, and prioritization.
Behavioral & LeadershipOnsite - NetflixEasyData ScientistSolve core probability and statistics questions
This problem tests your understanding of the Central Limit Theorem and its application in power analysis for A/B testing and confidence interval estimation.
Statistics & MathOnsiteProbabilityA/B TestingCentral Limit Theorem - NetflixMediumData ScientistWrite SQL for rolling frequency caps
This question evaluates proficiency with rolling-window analytics, frequency cap logic, time-based attribution, and per-user/per-campaign aggregation for advertising data.
Data Manipulation (SQL/Python)Onsite - New RelicMediumBackend EngineerCompress a String by Run-Length Counts, Keeping the Original When Not Shorter
Implement run-length string compression that replaces each run of repeated characters with the character and its count, returning the original string when the compressed form is not strictly shorter. Tests careful run handling, multi-digit counts, the tie rule, and complexity and edge-case discussion.
Coding & AlgorithmsOnsite
Netflix