Google·Data Scientist·Technical Phone Screen·Senior

SeniorPrefer not to say

Apr 2026

Summary

Google Data Scientist interview with a coding-heavy technical phone screen. The whole thing was basically one meaty array problem taken to its logical extremes, which I did not fully expect going in.

Questions Asked (1)

Given an integer array and a target value k, find the longest contiguous subarray whose elements sum to exactly k. Return its length and the start/end indices. Break ties by choosing the earliest start index, then the earliest end index.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

Started with the brute force and they let me finish it before asking for something better, which was nice.

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AI HintsAI Generated

Suggested Approach

Use a hash map to store the earliest index where each prefix sum occurs, then iterate through the array to find the longest subarray summing to k by checking if prefix_sum - k exists in the map. Handle tie-breaking by updating only when a longer length is found, or when equal length with an earlier start index, and ensure the earliest end index is naturally chosen by scanning left to right.

Pro tip: Emphasize that storing only the first occurrence of each prefix sum is crucial for maximizing subarray length, and explicitly discuss how to handle ties by comparing start indices when lengths are equal.

1. Clarify requirements and edge cases

Confirm that the array can contain negative numbers, zeros, and that k can be any integer. Discuss edge cases like empty array, no valid subarray, and multiple valid subarrays with the same length.

2. Design prefix sum + hash map approach

Explain that we compute prefix sums and use a hash map to store the earliest index for each prefix sum. For each index, check if (current_prefix_sum - k) exists in the map to find a subarray summing to k.

3. Handle tie-breaking rules

When a valid subarray is found, compare its length with the current best. If longer, update. If equal length, choose the one with the earlier start index; if start indices are equal, the earlier end index is automatically chosen because we scan left to right.

4. Implement and test

Write clean code with clear variable names, and test with provided examples and edge cases. Walk through a small example to demonstrate correctness.

5. Analyze complexity and trade-offs

State that time complexity is O(n) and space complexity is O(n) due to the hash map. Discuss alternative approaches like brute force (O(n^2)) and why the prefix sum method is optimal.

Key Points to Mention

Prefix sum technique to convert subarray sum to difference of two prefix sums.
Hash map storing the earliest index of each prefix sum to maximize subarray length.
Tie-breaking logic: prioritize longer length, then earlier start index, then earlier end index.
Time and space complexity analysis: O(n) time, O(n) space.
Handling of negative numbers and zeros, which makes sliding window infeasible.
Edge cases: empty array, no valid subarray, multiple valid subarrays with same length.

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