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C3 AI·Data Scientist·Technical Phone Screen·Intermediate

Intermediate
Jul 2026

Summary

Interviewed for a Data Scientist role at C3 AI and got a coding problem that looked straightforward but had enough edge cases to trip you up if you weren't careful. The divide-and-conquer angle wasn't the first thing I reached for.

Questions Asked (1)

Q1

Given a string and an integer k, find the length of the longest substring where every distinct character appears at least k times.

Algorithms & Data Structures
Author's notes

My first instinct was a sliding window, which doesn't actually work cleanly here because the validity condition is weird.

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AI HintsAI Generated

Suggested Approach

Use a divide-and-conquer strategy: recursively split the string at characters that appear fewer than k times, and return the maximum length of valid substrings. Alternatively, use a sliding window with a fixed number of distinct characters, iterating over possible distinct counts. Discuss trade-offs between approaches.

Pro tip: Start by clarifying edge cases (e.g., k=1, empty string) and then explain the divide-and-conquer approach, as it's often more intuitive and efficient for this problem. Mention that the sliding window approach has O(26*n) time complexity, which is effectively O(n) for lowercase letters.

1. Understand the problem and edge cases

Restate the problem in your own words and discuss edge cases such as k=1, empty string, or when no substring satisfies the condition. This shows thoroughness.

2. Choose an approach

Decide between divide-and-conquer and sliding window. Explain why you chose one over the other, considering time and space complexity.

3. Outline the algorithm

For divide-and-conquer: recursively split at characters with frequency < k. For sliding window: iterate over possible distinct character counts and use a window to track frequencies.

4. Analyze complexity

State the time and space complexity of your chosen approach. For divide-and-conquer, it's O(n) on average; for sliding window, O(26*n) = O(n).

5. Test with examples

Walk through a small example to verify correctness, and mention potential pitfalls like off-by-one errors or handling of non-alphabetic characters.

Key Points to Mention

  • Divide-and-conquer: split at characters with frequency < k, recursively solve subproblems.
  • Sliding window: fix the number of distinct characters and use two pointers to maintain a window where all characters appear at least k times.
  • Time complexity: O(n) for divide-and-conquer (average), O(26*n) for sliding window.
  • Space complexity: O(1) for sliding window (fixed alphabet), O(n) for recursion stack in divide-and-conquer.
  • Edge cases: k=1 (whole string), k > string length (0), empty string (0).
  • Optimization: early termination if remaining length <= current max.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.