Prepare for your next interview.

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1. Coding questions · The Trade Desk

   Implement monotonic-array linear interpolation

   This question evaluates proficiency with piecewise-linear interpolation on strictly increasing (monotonic) arrays, sound handling of out-of-range queries (error, clamp, extrapolate, or None/NaN), and efficient interval search over sorted data with a target of O(log n). It also probes real-world judgment about when each out-of-range policy is appropriate and which non-bisect strategies exist.

2. Coding questions · Apple

   Implement most_frequent_key without using max()

   This question evaluates proficiency in Python fundamentals and object-oriented inheritance, focusing on frequency aggregation using a precomputed dictionary, iteration over mappings, and correct handling of ties and empty inputs.

3. Coding questions · Meta

   Implement Multi-Level In-Memory Services

   This question evaluates a candidate's ability to design and implement mutable in-memory data structures and algorithms for stateful service simulations, covering account and file modeling, temporal operations with lazy expiration, ranking queries, merging entities, and capacity constraints.

4. Coding questions · Ramp

   Implement multi-level task manager APIs

   This question evaluates implementation skills for stateful in-memory data structures, API evolution handling, substring search and prioritized sorting, and time-windowed assignment logic with quota enforcement in the Coding & Algorithms domain, and is primarily a practical application problem rather than a purely conceptual one.

5. Coding questions

   Implement multiplication without using the multiplication operator

   This question evaluates proficiency in bitwise arithmetic, integer overflow semantics, sign handling, and algorithmic efficiency for implementing multiplication without using multiplication or division operators.

6. Coding questions · Intuit

   Implement nth Fibonacci number

   Implement nth Fibonacci number 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 · Nextdoor

   Implement ordering with dependency constraints

   This question evaluates understanding of dependency resolution and ordering within graph-based problems, including cycle detection, lexicographic tie-breaking, and extensions requiring certain items to appear as contiguous groups.

8. Coding questions · Lyft

   Implement paginated retrieval of transactions

   Implement paginated retrieval of transactions 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.

9. Coding questions · Peregrine

   Implement pagination and clump grouping

   This question evaluates practical skills in paginated API integration, data aggregation and grouping (clump formation), ID-to-name resolution with caching, error and rate-limit handling, and designing unit tests and complexity analysis within the Data Manipulation (SQL/Python) domain.

10. Coding questions · Boston Consulting Group

    Implement palindrome check and valid parentheses

    This question evaluates string-processing skills, algorithmic reasoning, and attention to edge cases by asking for a palindrome detector and a parentheses-sequence validator.

11. Coding questions · Zillow

    Implement placeholder-based pattern matcher

    Implement placeholder-based pattern matcher 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.

12. Coding questions · Coursera

    Implement Plurality and Runoff Voting

    This question evaluates understanding of voting algorithms, tie-breaking rules, ballot processing, and correctness under edge cases such as incomplete or exhausted ballots, and is commonly asked to assess algorithmic implementation, state simulation, and careful handling of corner cases in interview settings.

13. Coding questions · Coinbase

    Implement Plus One

    This question evaluates array manipulation and numeric carry propagation skills, along with the ability to reason about time and space complexity when performing arithmetic on digit lists.

14. Coding questions · Bitkernel

    Implement popup and redirect in JavaScript

    This question evaluates proficiency with client-side JavaScript, including browser APIs, DOM-based UI creation for popups, event handling, navigation mechanisms, and simple input validation for redirects.

15. Coding questions · DRW

    Implement portfolio optimization simulation

    This question evaluates proficiency in numerical simulation, portfolio optimization, time-series data processing, and computation of risk-return metrics such as expected return, volatility, and the Sharpe ratio.

16. Coding questions · Point72

    Implement Portfolio Trading Optimizer

    This question evaluates algorithmic problem-solving, array processing, input validation via decorators, and the ability to produce concise transaction reports for maximizing non-overlapping buy/sell profits.

17. Coding questions · Meta

    Implement power and balance-parentheses algorithms

    This question evaluates algorithmic design and analysis skills, covering fast exponentiation with attention to numerical edge cases and precision, and minimal-removal parentheses balancing with string-processing and data-structure reasoning.

18. Coding questions · Mixpanel

    Implement precise string-based decimal addition

    This question evaluates a candidate's proficiency in string-based arbitrary-precision arithmetic, including decimal alignment, fractional carry propagation, normalization of numeric strings, and analysis of time and space complexity.

19. Coding questions · Ansys

    Implement Prefix Search and Node Removal

    This question evaluates proficiency in string data structures and manipulation (prefix-search concepts including case-insensitive matching and regex-based normalization) as well as linked list pointer manipulation and in-place node removal.

20. Coding questions · Optiver

    Implement price-based order matcher

    This question evaluates competency in data structures and algorithmic design for price-based order matching systems, including priority-based matching, efficient order book maintenance, and deterministic tie-breaking requirements.

21. Coding questions · Airbnb

    Implement prioritized refund allocation engine

    This question evaluates algorithmic problem-solving, data modeling, and implementation skills for prioritized refund allocation, including parsing inputs, grouping by payment method, sorting by date, aggregating remaining balances, and handling partial fulfillment and edge cases; it is commonly asked to assess the ability to implement ordered, constraint-driven allocation logic while reasoning about correctness and performance. It belongs to the Coding & Algorithms domain and represents a practical implementation problem emphasizing applied algorithmic reasoning and complexity analysis rather than purely conceptual discussion.

22. 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.

23. 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.

24. 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.