Data Scientist Interview Questions

Showing 1–8 of 8 results

• CoinbaseMedium·Data Scientist
  Detect sequence rule and repair anomaly

  This question evaluates a candidate's skill in sequence pattern recognition, algorithm design, complexity analysis, and robust integer arithmetic by requiring inference among arithmetic, alternating-difference, geometric, and Fibonacci-plus-constant models while tolerating at most one corrupted term under O(n) time and O(1) extra space constraints.

  Coding & AlgorithmsHR Screen
• Morgan StanleyMedium·Data Scientist
  Implement Factorial and Squares

  A Morgan Stanley data scientist HR-screen live-coding warm-up: implement Python `factorial(n)` (iteratively, then explain the recursive version) and `squares(n)` returning the squares of the first n integers. Evaluates clean Python, the iteration-vs-recursion trade-off, time and space complexity analysis, input validation, and edge cases like n = 0 and negative input.

  Coding & AlgorithmsHR Screen
• NVIDIAHard·Data Scientist
  Design and explain robust web APIs for ML inference

  This question evaluates a candidate's proficiency in designing HTTP REST APIs for ML inference, including API endpoints, versioning, idempotency, request/response schemas, authentication/authorization, rate limiting, observability, and backward-compatibility policies, and it falls under the Coding & Algorithms domain for a data scientist role.

  Coding & AlgorithmsHR Screen
• NVIDIAHard·Data Scientist
  Implement CUDA-tiled matrix multiplication and explain architecture

  This question evaluates a candidate's competency in CUDA GPU programming, parallel algorithms, and performance engineering for FP32 matrix multiplication, covering tiling strategies, memory hierarchy (global/shared/register), synchronization, numerical precision, and occupancy/resource analysis.

  Coding & AlgorithmsHR Screen
• NVIDIAHard·Data Scientist
  Optimize CUDA GEMM with tiling and coalescing

  This question evaluates proficiency in GPU programming and performance optimization, assessing understanding of the CUDA execution model, memory hierarchy and bank conflicts, occupancy limits, and practical kernel design concerns for single-precision GEMM including tiling, coalescing, vectorized memory accesses and benchmarking.

  Coding & AlgorithmsHR Screen
• NVIDIAHard·Data Scientist
  Reverse linked lists, including k-group

  This question evaluates understanding of linked list manipulation including pointer operations, in-place reversal techniques, recursion and stack-depth considerations, cycle detection, and time/space complexity analysis.

  Coding & AlgorithmsHR Screen
• SIG (Susquehanna)Medium·Data Scientist
  Compute bus-on-time and dice-sum probabilities

  This problem tests your ability to calculate probabilities involving continuous uniform distributions and discrete combinations of independent events.

  Coding & AlgorithmsHR ScreenProbabilityCombinatoricsUniform Distribution
• TikTokMedium·Data Scientist
  Implement streaming SRM detector with late events

  This question evaluates proficiency in stateful stream processing, statistical anomaly detection for sample ratio mismatch, and scalable system design concerns such as deduplication, late/out-of-order event handling, real-time aggregation, chi-square testing with Yates correction, bot-rate mitigation, sharding, and replay validation.

  Coding & AlgorithmsHR Screen