Snapchat interview questions

Showing 1–30 of 94 results

• Analyze OLS After Duplicating Every ObservationMedium

  This question tests your understanding of OLS coefficient estimation and standard error calculations under the scenario of duplicate data observations.

  SnapchatData ScientistStatistics & MathTechnical Screen
• Calculate Average Camera Switches per SessionMedium

  Tests the ability to write a PostgreSQL query using window functions (LAG) to compute the average number of specific state transitions per session while accounting for zero-transition sessions and avoiding integer division.

  SnapchatData ScientistData Manipulation (SQL/Python)Technical Screen
• Check if a binary tree is completeMedium

  This problem tests your understanding of binary tree properties and your ability to perform a level-order traversal to verify structural completeness.

  SnapchatSoftware EngineerCoding & AlgorithmsTechnical Screen
• Compare Batch Normalization and Layer NormalizationHard

  Compare batch and layer normalization by their axes, learned parameters, running statistics, batch-size effects, and training-to-inference debugging.

  SnapchatMachine Learning EngineerMachine LearningOnsite
• Compare WebSocket, SSE, and long pollingHard

  This question tests a software engineer's depth in web networking fundamentals, covering real-time communication protocols and the OSI and TCP/IP models. It assesses practical knowledge of WebSocket, SSE, and long polling trade-offs, as well as understanding of how modern transport protocols like QUIC differ from TCP in multiplexing, handshake latency, and connection migration.

  SnapchatSoftware EngineerSoftware Engineering FundamentalsOnsite
• Compare convolutions and transformersMedium

  This question evaluates understanding of neural network architectures, focusing on inductive biases, data and compute trade-offs, mechanisms for handling long-range dependencies, domain-specific roles in vision and NLP, and modern hybrid approaches that address architecture limitations.

  SnapchatMachine Learning EngineerMachine LearningTechnical Screen
• Compute CTR and metrics with pandasMedium

  This question evaluates proficiency in time-series and event-level data manipulation with pandas, including CTR computation, event denoising and deduplication, sessionization, cohort analysis, temporal joins, and performance-aware vectorized operations within the Data Manipulation (SQL/Python) domain.

  SnapchatData ScientistData Manipulation (SQL/Python)Onsite
• Compute User Retention and Analyze Event DataMedium

  This question evaluates a candidate's ability to perform SQL and Python data manipulation for event analytics, including cohort retention, aggregation of distinct purchasing users, median-of-daily-events calculations, and hourly time-series grouping.

  SnapchatData ScientistData Manipulation (SQL/Python)Onsite
• Compute islands in a binary gridMedium

  This question evaluates a candidate's competency in modeling grids as graphs, detecting connected components, applying graph traversal algorithms (DFS/BFS) and disjoint-set (Union-Find) data structures, and analyzing algorithmic time and space complexity.

  SnapchatSoftware EngineerCoding & AlgorithmsOnsite
• Compute longest increasing path in matrixHard

  This question evaluates algorithmic problem-solving skills in graph traversal and dynamic programming on matrices, measuring understanding of state representation and performance trade-offs in grid-based searches within the Coding & Algorithms domain.

  SnapchatSoftware EngineerCoding & AlgorithmsOnsite
• Compute same-day acceptance metrics last weekMedium

  This question evaluates proficiency in time-based data manipulation, SQL JOINs and aggregations, handling NULLs and missing reference rows, and computing acceptance and percentage metrics with careful UTC date boundary treatment.

  SnapchatData ScientistData Manipulation (SQL/Python)Technical Screen
• Compute shortest path in a 2D gridHard

  This question evaluates understanding of graph traversal and pathfinding concepts, including modeling a 2D grid as a graph and reasoning about shortest-path computations and obstacle handling.

  SnapchatSoftware EngineerCoding & AlgorithmsOnsite
• Compute shortest recursive string encodingMedium

  This question evaluates proficiency in string manipulation, pattern detection, recursion, and dynamic programming for efficient sequence compression in the Coding & Algorithms domain.

  SnapchatSoftware EngineerCoding & AlgorithmsOnline Assessment
• Compute sliding window medianMedium

  This question evaluates the ability to maintain a running median over a sliding window, testing competencies in data structures, order statistics, dynamic updates, and algorithmic efficiency within the Coding & Algorithms domain.

  SnapchatSoftware EngineerCoding & AlgorithmsTechnical Screen
• Count Grid Islands That Never Touch the BorderMedium

  Coding problem on a binary grid where 0 marks land and 1 marks water: count the islands, connected horizontally or vertically, that have no cell on the grid's border. It tests grid traversal, connected components and careful handling of islands that reach the edge through a single cell.

  SnapchatSoftware EngineerCoding & AlgorithmsOnsite
• Count Users Whose First Daily Event Is App LaunchMedium

  Write a PostgreSQL query to identify each user's first event per calendar day and aggregate the distinct user count by operating system and device when that first event is an app launch. Tests window functions, tie-breaking logic, and multi-dimensional grouping.

  SnapchatData ScientistData Manipulation (SQL/Python)Technical Screen
• Count islands with eight-direction adjacencyMedium

  This question evaluates a candidate's competency in graph traversal algorithms and data-structure trade-offs by counting connected components on a grid with eight-direction adjacency, focusing on BFS/DFS behavior and optional Union-Find approaches.

  SnapchatSoftware EngineerCoding & AlgorithmsTechnical Screen
• Count ways to decode digit stringHard

  This question evaluates a candidate's skill in dynamic programming and combinatorial reasoning about string partitioning, testing competency in counting valid decodings under constraint handling and edge-case analysis.

  SnapchatSoftware EngineerCoding & AlgorithmsOnsite
• Describe a challenging project you ledMedium

  This question evaluates leadership, project management, stakeholder communication, and technical problem-solving skills in a machine learning engineering context, with emphasis on trade-off analysis and impact measurement.

  SnapchatMachine Learning EngineerBehavioral & LeadershipTechnical Screen
• Design A/B Tests for Banner Ad and Group-Story FeatureMedium

  Evaluates A/B test design for a banner ad and a group-story feature in a social app. Strong answers define monetization, engagement, safety, and retention metrics, handle accidental clicks for ads, account for network effects in group stories, and set launch criteria with guardrails.

  SnapchatData ScientistAnalytics & ExperimentationOnsite
• Design a Column-Queryable KV DatabaseMedium

  This problem tests your ability to design a distributed key-value storage system that supports efficient column-based filtering and range scans, balancing write performance against analytical query capabilities.

  SnapchatSoftware EngineerSystem DesignOnsite
• Design a Metrics SystemMedium

  Design a high-throughput, low-latency metrics collection, aggregation, and querying platform. The question tests your ability to handle multi-dimensional time-series data, mitigate high-cardinality label explosions, and design tiered storage for varying query windows.

  SnapchatSoftware EngineerSystem DesignOnsite
• Design a News AggregatorHard

  This question evaluates a candidate's ability to design scalable content ingestion and distribution systems, encompassing API-driven fetching, scheduling, deduplication, storage, ranking, freshness guarantees, API rate limiting, and efficient article serving.

  SnapchatSoftware EngineerSystem DesignOnsite
• Design a Pre-Login Risk and Challenge ServiceMedium

  Design a low-latency, resilient pre-login security service that evaluates risk signals, issues dynamic verification challenges, and verifies responses without exposing authentication flows to replay attacks.

  SnapchatSoftware EngineerSystem DesignOnsite
• Design a Product Tagging PipelineMedium

  This problem tests your ability to design a scalable multi-modal machine learning pipeline that processes diverse content types to generate standardized taxonomy tags for an e-commerce platform.

  SnapchatMachine Learning EngineerML System DesignOnsite
• Design a Trustworthy Ranking SystemMedium

  This problem tests the ability to design an end-to-end ML system for ranking content while balancing engagement metrics with safety, misinformation, and user trust.

  SnapchatMachine Learning EngineerML System DesignOnsite
• Design a device owner lookup serviceMedium

  This question tests the ability to design a distributed system for tracking the mapping between ephemeral devices and their currently signed-in users, focusing on handling event concurrency and high-throughput read/write operations.

  SnapchatSoftware EngineerSystem DesignOnsite
• Design a harmful content detection systemHard

  This question evaluates proficiency in ML system design for harmful-content detection, assessing competencies in multimodal modeling, taxonomy and labeling strategies, data strategy, privacy-aware architecture, real-time inference, human-in-the-loop decisioning, and operational reliability for global consumer platforms.

  SnapchatMachine Learning EngineerML System DesignOnsite
• Design a metrics collection and alerting systemMedium

  This question evaluates system design competencies such as scalable time-series data modeling, ingestion and storage architecture, query latency versus retention trade-offs, and alert evaluation logic within the System Design domain.

  SnapchatSoftware EngineerSystem DesignOnsite
• Design a ranking system pipelineHard

  This question evaluates competency in end-to-end ML system design for ranking and recommendation, covering problem definition, data and feature pipelines, offline training, online inference, model refresh, monitoring, and handling cold-start, exploration, feedback loops, and model drift.

  SnapchatMachine Learning EngineerML System DesignTechnical Screen