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Coding & Algorithms interview questions

3276 Coding & Algorithms questions from 366 companies, with hints, runnable code and solution walkthroughs.

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273 easy2539 medium464 hard

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Coding & Algorithms interview questions by the numbers

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Katkat has 3,276 Coding & Algorithms interview questions from 366 companies; the most come from Amazon (7%), Meta (7%) and Google (6%). By difficulty: 8% easy, 78% medium and 14% hard. The most common round is Technical Screen (52%). Frequent concepts include Algorithms, Data Structures, Arrays and Greedy.

Companies (366)

Difficulty

  • Easy8% · 273
  • Medium78% · 2539
  • Hard14% · 464

Interview rounds

  • Technical Screen52% · 1706
  • Onsite33% · 1080
  • Online Assessment13% · 427
  • HR Screen1% · 37
  • Other1% · 26

Roles

  • Software Engineer80% · 2629
  • Machine Learning Engineer8% · 253
  • Data Scientist7% · 241
  • Data Engineer1% · 45
  • Backend Engineer1% · 26

Frequent concepts

  • Algorithms9% · 302
  • Data Structures7% · 228
  • Arrays5% · 176
  • Greedy5% · 164
  • Optimization5% · 151
  • Hash Map4% · 124

Showing 2731–2760 of 3276 results

  • From a Squarepoint technical screen: one move adds 1 to every element of an integer array except one chosen element, and you must find the fewest moves that make all elements equal. It tests reasoning about what each move really changes, along with negative values and answers beyond the 32-bit range.

    SquarepointData ScientistCoding & AlgorithmsTechnical Screen
  • Determine all unique values from an odd-length array whose removal leaves an even-length array that can be partitioned into pairs with minimum total absolute difference.

    SquarepointQuantitative ResearcherCoding & AlgorithmsTechnical Screen
  • Tests two-pointer traversal across two distinct sorted arrays to find a target sum, emphasizing linear time complexity and integer overflow prevention.

    SquarepointRisk Technology Software EngineerCoding & AlgorithmsTechnical Screen
  • Tests string traversal, frequency counting, and deterministic tie-breaking under large input constraints.

    SquarepointSoftware EngineerCoding & AlgorithmsHR Screen
  • This problem tests your ability to manipulate time-series data using vectorized operations and implement iterative numerical approximations for square roots.

    SquarepointQuantitative TraderCoding & AlgorithmsTechnical Screen
  • This question evaluates a candidate's algorithmic problem-solving skills across array and time-series processing, greedy optimization, and dynamic programming, requiring implementation and complexity analysis of maximum drawdown, single-trade profit, and coin change problems within the Coding & Algorithms domain for a Data Scientist role.

    SquarepointData ScientistCoding & AlgorithmsTechnical Screen
  • This question evaluates algorithmic problem-solving skills, particularly efficient array processing and profit-optimization across single-transaction and multiple-transaction variants, along with time and space complexity analysis.

    SquarepointData ScientistCoding & AlgorithmsTechnical Screen
  • This question evaluates algorithmic problem-solving and optimization competencies focused on dynamic resource allocation, revenue maximization, and designing efficient solutions that scale with large n, m, and quantities.

    SquarepointData ScientistCoding & AlgorithmsOnline Assessment
  • This question evaluates proficiency in robust file parsing, schema-driven data modeling, type conversion, validation, duplicate handling, and implementing aggregate and ranking queries using Python's standard library for messy, delimited payroll data.

    SquarepointSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This problem tests your ability to perform a two-pass linear scan on an array to compute an aggregate statistic and filter elements, emphasizing space complexity and data integrity.

    SquarepointSoftware EngineerCoding & AlgorithmsHR Screen
  • Determine the minimum length of a contiguous subarray that contains at least k distinct elements. This problem tests sliding-window techniques, hash map management, and linear-time optimization.

    SquarepointQuantitative ResearcherCoding & AlgorithmsTechnical Screen
  • This question set evaluates algorithmic optimization and string-processing skills: the first problem focuses on maximizing cumulative revenue from limited inventories (optimization and greedy reasoning with dynamic value updates), while the second focuses on case-insensitive text parsing, word frequency counting, and frequency-based ordering.

    SquarepointSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This question evaluates understanding of dictionary/hash table performance characteristics, covering hashing, collision-resolution strategies, load factor and resizing impacts, and the cost of iterating or copying keys into a dynamic-array-backed list within the Coding & Algorithms/data structures domain.

    StackAdaptSoftware EngineerCoding & AlgorithmsHR Screen
  • This question evaluates a candidate's ability to design efficient data structures and algorithms for a time-windowed key-value store, focusing on expiration handling, update semantics, and maintaining aggregate metrics under memory constraints.

    StackAdaptSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to maintain dynamic statistics in a data stream using efficient heap-based data structures.

    StackAdaptMachine Learning EngineerCoding & AlgorithmsTechnical Screen
  • Reconstruct a binary tree with distinct values from its preorder and inorder traversals and return it in level-order form with null markers. Tests how the two traversal orders pin down structure, careful index bookkeeping, and efficient handling of deep, skewed trees.

    StackAdaptMachine Learning EngineerCoding & AlgorithmsOnsite
  • This question evaluates proficiency in implementing core neural-network primitives (ReLU, numerically-stable Softmax, LayerNorm, BatchNorm with running statistics, and RMSNorm), numerical stability and normalization concepts, and understanding of autograd-compatible tensor operations.

    Startups.ComMachine Learning EngineerCoding & AlgorithmsOnsite
  • Given elevation samples taken at regular intervals, return the start and end indices of the first climb, first under strict rules where elevation may never drop and then allowing a temporary descent limited to a fraction of the gain so far. Tests precise index semantics, lookahead and careful state tracking.

    StravaSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates proficiency with version control diffs, repository library APIs, file I/O and CSV parsing, and data aggregation to map changed files to their owners.

    StripeSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests the ability to manage task scheduling with specific affinity constraints and varying worker processing times using an efficient priority-based simulation.

    StripeSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Design and implement an in-memory account ledger that supports deposits, transfers, and platform-backed lending with automatic debt repayment.

    StripeSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to efficiently process and aggregate time-series usage data while handling complex proration rules and tiered pricing models.

    StripeSoftware EngineerCoding & AlgorithmsOnline Assessment
  • Implement a fee calculation engine that parses CSV transaction records, applies multi-attribute pricing rules and merchant volume discounts, and accurately rounds fee amounts in cents.

    StripeSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates stateful transaction processing and aggregation skills, including per-(account,currency) balance maintenance, timestamp-based ordering, rejection rules, and overdraft coverage via a platform account.

    StripeSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests the ability to manage stateful financial records while enforcing conditional logic, fee structures, and balance validation.

    StripeSoftware EngineerCoding & AlgorithmsOnsite
  • Stripe software-engineer onsite coding question: design data structures and algorithms to compute currency conversions from pairwise exchange rates. It tests modeling currencies as a weighted directed graph, chaining rates with BFS/DFS to answer queries (or -1 when unknown), supporting online updates and many queries efficiently, detecting contradictions and arbitrage in cycles, and computing all rates against a base via topological sort on a DAG, with time and space complexity analysis.

    StripeSoftware EngineerCoding & AlgorithmsOnsite
  • Evaluates implementation-level algorithmic logic for tiered pricing, covering per-unit aggregation, interval reasoning, and mixed incremental vs fixed pricing models within the Coding & Algorithms domain and Data Engineering role; abstraction level is practical, implementation-focused business logic and data transformation.

    StripeData EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates skills in binary-to-text data representation, bitmap rendering, and efficient string and array manipulation for output formatting.

    StripeSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates event-driven scheduling, deterministic time-based ordering, stateful account updates for plan changes and renewals, and algorithmic merging of notification streams in the Coding & Algorithms domain.

    StripeSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Implement an access-control evaluator that parses rule strings with conditions and returns the first matching decision (ACCEPT or BLOCK).

    StripeSoftware EngineerCoding & AlgorithmsTechnical Screen

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