Coding questions

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1. Coding questions · Roblox

   Implement Python Function for Statistical Test P-Values

   This question evaluates proficiency in statistical hypothesis testing, p-value interpretation, and implementing distribution-based calculations (Z and Student-t) in code, and it falls under the Coding & Algorithms domain for data scientist roles.

2. Coding questions · Anthropic

   Implement Python LRU cache with args and persistence

   This question evaluates a candidate's ability to design and implement an LRU cache in Python that supports variable-length positional and keyword arguments with canonical, deterministic hashing for semantically equivalent calls and O(1) get/put via a hash map plus a doubly linked list; it falls under the Coding & Algorithms domain and primarily tests practical implementation skills, API robustness, hashing/equality subtleties, and algorithmic complexity guarantees. The persistence follow-up evaluates understanding of serialization and storage design — on-disk formats, versioning, and atomic write strategies — and compares trade-offs between binary pickle and JSON-based serialization in terms of security, compatibility, and performance, reflecting both conceptual design and practical system-level considerations.

3. Coding questions · Amazon

   Implement PyTorch training loop

   This question evaluates practical implementation skills in PyTorch, focusing on model and device management, batch-wise training mechanics, gradient handling, and optimizer interaction.

4. Coding questions · Roblox

   Implement queue-based rate limiter with multi-key limits

   This question evaluates implementation and design skills around rate limiting, including rolling-window counters, multi-key constraints, and atomic updates, and falls under the Coding & Algorithms domain focused on practical application of algorithms and data structures.

5. Coding questions · Meta

   Implement randomized Quickselect without k-shift bug

   This question evaluates understanding of randomized Quickselect and selection algorithms, including in-place partition semantics for the k-th largest element, careful index and k-update reasoning to prevent k-shift/off-by-one bugs, handling duplicates and adversarial pivots, and analysis of expected versus worst-case time and auxiliary space.

6. Coding questions · Meta

   Implement range-sum tree and sort merged lists

   Implement range-sum tree and sort merged lists evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

7. Coding questions · Uber

   Implement rate limiter, top-K, scheduler algorithms

   This question evaluates proficiency in concurrent programming and thread-safe design, core algorithm implementation (binary search and top-K logic), data structure usage (including doubly-linked-list techniques), and scheduling and ranking reasoning for meeting and resource allocation.

8. Coding questions · Atlassian

   Implement Real-Time Rate Limiting for Web Service Requests

   This question evaluates understanding of real-time rate limiting, time-windowed traffic control, and efficient per-client state management under algorithmic constraints.

9. Coding questions · Amazon

   Implement Reservoir Sampling; Analyze Time and Space Complexity

   This question evaluates understanding of streaming randomized algorithms and probabilistic reasoning—specifically reservoir sampling—along with analysis of time and space complexity and use of hash-based structures for duplicate detection; it is in the Coding & Algorithms domain and tests both conceptual probability invariants and practical implementation skills. Such problems are commonly asked to gauge a candidate's ability to design one-pass, linear-time solutions for unbounded data streams and to reason about algorithmic correctness and resource bounds in technical interviews.

10. Coding questions · Meta

    Implement right side view and local minimum search

    This question evaluates a candidate's understanding of binary tree traversal and array local-minimum detection, measuring skills in data structures (binary trees and arrays), algorithm design, and algorithmic time-complexity analysis.

11. Coding questions · Tencent

    Implement robust k-means with k-means++ initialization

    This question evaluates implementation and understanding of clustering algorithms (k-means with k-means++), vectorized numerical computing with NumPy, handling of edge cases such as empty clusters and sample weighting, and algorithmic complexity analysis in the Coding & Algorithms domain for Data Scientist roles.

12. Coding questions · Microsoft

    Implement rotated array binary search with duplicates

    This question evaluates algorithm design and analysis skills, focusing on binary-search variants, handling duplicates in rotated non-decreasing arrays, rotation-index reasoning, and rigorous edge-case analysis; domain: Coding & Algorithms, specifically search algorithms and array manipulation.

13. Coding questions · Apple

    Implement rotation, LRU cache, streaming median, cycle detection

    This question evaluates understanding of array/matrix manipulation, cache and data structure design, streaming algorithms for median maintenance, and graph theory for cycle detection, with emphasis on algorithmic complexity analysis and handling of edge cases.

14. Coding questions · DoorDash

    Implement round-robin load balancer

    This question evaluates a candidate's ability to implement a strict round-robin load balancer with O(1) average operations while handling concurrent nextServer and update calls, health-check-driven skipping, and failure scenarios, testing competencies in data structures, concurrent programming, and fault-tolerant system behavior.

15. Coding questions · Databricks

    Implement run-length encoding and decoding

    This question evaluates proficiency in string manipulation and encoding algorithms, specifically run-length encoding and decoding, along with attention to edge cases such as empty inputs and single-character runs and correct handling of repetition counts.

16. Coding questions · Pinterest

    Implement scalable prime generator

    This question evaluates a candidate's ability to implement scalable prime generation and related algorithmic optimization, including algorithm selection, time and memory complexity reasoning, edge-case handling, and verification via unit tests.

17. Coding questions · Adobe

    Implement scalable word count locally

    This question evaluates understanding of scalable word-count processing, including tokenization and normalization rules, streaming or external-memory techniques for inputs larger than RAM, and efficient top‑K frequency computation.

18. Coding questions · Meta

    Implement scaled dot-product attention

    This question evaluates a candidate's ability to implement single-head scaled dot-product attention, including correct matrix operations for Q, K, V, masked attention handling, and numerically stable softmax, testing competencies in linear algebra and machine learning model internals within the Coding & Algorithms / Machine Learning domain.

19. Coding questions · NVIDIA

    Implement simple VM manager with CRUD operations

    This question evaluates a candidate's ability to design and implement in-memory data models and CRUD APIs with unique-identifier management and consistent error signaling, testing skills in data structures, API/interface design, and algorithmic complexity.

20. Coding questions · Snapchat

    Implement sin(x) with precision constraints

    This question evaluates understanding of numerical methods, floating-point arithmetic, and algorithmic implementation in the Coding & Algorithms domain by requiring an approximation of the sine function under explicit error bounds.

21. Coding questions · PayPal

    Implement 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.

22. Coding questions · Meta

    Implement sliding-window moving average

    This question evaluates a candidate's ability to implement an efficient streaming data structure and manage numerical precision and overflow when computing a sliding-window moving average.

23. Coding questions · Atlassian

    Implement sliding-window rate limiter with dual thresholds

    This question evaluates a candidate's skill in implementing efficient online sliding-window rate limiting, covering stream processing, time-based window management, per-key state maintenance, algorithmic complexity analysis, and formal correctness reasoning.

24. Coding questions · Bloomberg

    Implement sliding-window timestamped average

    This question evaluates understanding of time-based sliding-window data structures, streaming aggregation, and the handling of timestamped records with efficient incremental updates and evictions.