Data Scientist Interview Questions

Showing 1–30 of 132 results

• AAdiaEasy·Data Scientist
  Compute Score Difference in Reversing Array Game

  This question tests the ability to manage state changes while iterating through an array based on index-dependent rules, specifically involving conditional array modifications.

  Coding & AlgorithmsTechnical ScreenArraysSimulationDeque
• Akuna CapitalMedium·Data Scientist
  Count subarrays equal to target

  This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Count subarrays equal to target states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  Coding & AlgorithmsTechnical Screen
• Akuna CapitalMedium·Data Scientist
  Maximize profitable pairs

  This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Maximize profitable pairs states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  Coding & AlgorithmsTechnical Screen
• AmazonMedium·Data Scientist
  Compute array modes with ties and no-mode rule

  This question evaluates algorithm design and data-structure skills—frequency counting, hashing, and handling edge cases such as ties and a no-mode rule—within the coding and algorithms domain for data scientist roles.

  Coding & AlgorithmsTechnical Screen
• AmazonMedium·Data Scientist
  Determine Length of Longest Unique Substring

  This question evaluates string-processing skills and algorithmic problem-solving, including handling character uniqueness and performance considerations. Commonly asked in Coding & Algorithms interviews to assess a candidate's ability to implement efficient solutions and reason about time/space trade-offs, it targets practical application rather than purely conceptual understanding.

  Coding & AlgorithmsTechnical Screen
• AmazonMedium·Data Scientist
  Generate Synthetic Clickstream Data with Python Function

  This question evaluates a candidate's ability to implement synthetic data generation and probabilistic event simulation in Python using libraries like pandas and numpy, emphasizing timestamp handling, random sampling, and feature engineering for clickstream records.

  Coding & AlgorithmsTechnical Screen
• AmazonMedium·Data Scientist
  Generate primes up to n efficiently

  This question evaluates algorithm design and complexity analysis for prime generation, focusing on sieving techniques and time-space trade-offs when producing primes up to large n.

  Coding & AlgorithmsTechnical Screen
• AmazonMedium·Data Scientist
  Implement Function to Determine Mode and Prime Numbers

  This question evaluates algorithmic problem-solving skills, including frequency analysis for mode computation, correct handling of ties and uniqueness edge cases, and basic number-theoretic competency for prime identification.

  Coding & AlgorithmsTechnical Screen
• AmazonMedium·Data Scientist
  Implement a high-throughput web crawler safely

  This question evaluates competency in concurrent systems, scalable data ingestion, and algorithmic design for a high-throughput web crawler, covering URL normalization, deduplication, per-host rate limiting, fault-tolerant checkpointing, and bounded-memory queueing.

  Coding & AlgorithmsTechnical Screen
• AmazonMedium·Data Scientist
  Solve Algorithmic Challenges in Online Coding Assessments

  This question evaluates proficiency in fundamental algorithmic problem-solving, specifically array manipulation, string processing, and the use of basic data structures along with performance and complexity reasoning.

  Coding & AlgorithmsTechnical Screen
• AmazonMedium·Data Scientist
  Solve Search Insert Position Using Binary Search

  This question evaluates proficiency in binary search, algorithmic implementation on sorted arrays, and understanding of time complexity and index management.

  Coding & AlgorithmsTechnical Screen
• AmazonMedium·Data Scientist
  Solve stock, BFS path, and merge intervals

  This question evaluates algorithmic problem solving across array scanning, BFS-based constrained shortest-path selection, and interval merging, with emphasis on time/space complexity reasoning, correctness proofs, and thorough edge-case handling. It is commonly asked to assess efficiency guarantees (e.g.

  Coding & AlgorithmsTechnical Screen
• AmazonEasy·Data Scientist
  Solve two string DP/hash problems

  This question set evaluates string-processing and algorithmic problem-solving skills, including encoding and transformation for unique representations and dynamic programming, memoization, and backtracking for enumerating all valid segmentations.

  Coding & AlgorithmsTechnical Screen
• AppleMedium·Data Scientist
  Find Maximum Sum of Contiguous Subarray Length k

  This question evaluates skill in array manipulation and computing aggregate metrics over fixed-length intervals, along with understanding of algorithmic complexity and trade-offs between runtime and memory.

  Coding & AlgorithmsTechnical Screen
• AtlassianMedium·Data Scientist
  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.

  Coding & AlgorithmsTechnical Screen
• B(Block (Square)Medium·Data Scientist
  Build referral chains and detect cycles

  This question evaluates graph algorithm competencies such as referral-chain traversal, cycle detection, handling noisy input data, and reasoning about time and space complexity for efficient per-node computation.

  Coding & AlgorithmsTechnical Screen
• Boston Consulting GroupMedium·Data Scientist
  Analyze Python Functions: Improve Readability and Efficiency

  This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Analyze Python Functions: Improve Readability and Efficiency states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  Coding & AlgorithmsTechnical Screen
• BByteDanceMedium·Data Scientist
  Compute Minimum Parentheses Additions

  This question evaluates proficiency in string processing and algorithmic reasoning for balancing parentheses, testing understanding of invariants and edge-case handling.

  Coding & AlgorithmsTechnical Screen
• BByteDanceMedium·Data Scientist
  Count Same-Day Registered Posters

  This question evaluates SQL querying skills, including joining relational tables, date handling, aggregation, and deduplicating users across events. Commonly asked in Coding & Algorithms interviews for data scientists, it assesses practical relational database querying and analytics tasks—filtering, grouping, and counting distinct users across tables—and tests practical application of SQL rather than purely conceptual database theory; this summary is in English.

  Coding & AlgorithmsTechnical Screen
• BByteDanceMedium·Data Scientist
  Determine Whether an Integer Is a Palindrome

  This problem tests your ability to manipulate integers mathematically to detect palindromic sequences without converting the number into a string, requiring careful handling of edge cases and integer overflow.

  Coding & AlgorithmsTechnical ScreenMathAlgorithmsInteger Manipulation
• BByteDanceMedium·Data Scientist
  Probability That One Fair Die Beats Another

  Solve a coding interview problem about the probability that one fair die beats another when the dice may have different sizes and duplicate face values. The challenge emphasizes strict tie handling and an efficient approach that avoids comparing every possible pair of faces.

  Coding & AlgorithmsTechnical Screen
• C3 AIHard·Data Scientist
  Find longest substring with at least k repeats

  This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Find longest substring with at least k repeats states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  Coding & AlgorithmsTechnical Screen
• C3 AIMedium·Data Scientist
  Longest Substring Where Every Character Appears at Least K Times

  Find the longest substring in which every present character appears at least k times. Practice divide-and-conquer splitting, frequency reasoning, and fixed-alphabet complexity.

  Coding & AlgorithmsTechnical Screen
• Capital OneMedium·Data Scientist
  Critique and Test Python Preprocessing Utilities Effectively

  This question evaluates a candidate's ability to review and critique Python preprocessing utilities, covering competencies in software design patterns (fit/transform separation), coding style and import hygiene, and unit-test specification for data-science pipelines.

  Coding & AlgorithmsTechnical Screen
• Capital OneMedium·Data Scientist
  Explain Shell Script Line-by-Line for Data Science Workflows

  This question evaluates familiarity with shell scripting for reproducible data-science workflows, Python object-oriented design including transformer patterns (fit/transform separation), outlier detection and imputation strategies, code-style critique, and unit testing competency.

  Coding & AlgorithmsTechnical Screen
• Capital OneMedium·Data Scientist
  Explain Shell Script for Python Virtual Environment Setup

  This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Explain Shell Script for Python Virtual Environment Setup states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  Coding & AlgorithmsTechnical Screen
• Capital OneMedium·Data Scientist
  Fix failing tests and refactor code

  This question evaluates a candidate's ability to debug, test, and refactor Python code with attention to state management, mutable default arguments, deterministic unit testing, API design, and type-safety.

  Coding & AlgorithmsTechnical Screen
• CCargurusMedium·Data Scientist
  Reverse a Character Array In Place

  This problem tests the ability to manipulate array elements in-place using two-pointer logic while adhering to strict space complexity constraints.

  Coding & AlgorithmsTechnical ScreenArraysTwo PointersIn-place
• CitadelMedium·Data Scientist
  Implement Infinite Fibonacci Generator Using Lazy Evaluation

  This question evaluates understanding of lazy evaluation and Python generator semantics, testing a candidate's ability to work with iterative sequence production and manage state across iterations.

  Coding & AlgorithmsTechnical Screen
• CitadelMedium·Data Scientist
  Implement Piecewise Linear Interpolation and Extrapolation

  Implement piecewise linear interpolation from unsorted knots, including exact-knot behavior and endpoint extrapolation. Practice paired sorting, binary search, and numerical edge cases.

  Coding & AlgorithmsTechnical Screen