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IMC·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Jul 2026

Summary

Did a technical screen for a Quant Engineer role at IMC. One coding problem, felt pretty algorithmic in nature, and the interviewer clarified the spec partway through which was actually helpful.

Questions Asked (1)

Q1

Given a stream of events where each event has a timestamp, a category, and a quantity, compute the running 'reduction' metric over time. Recycled quantities count positive, waste quantities count negative. Return either the maximum reduction reached at any point, or the full running series, depending on what the interviewer asks.

Algorithms & Data StructuresProduct Analytics & Metrics
Author's notes

The problem sounds vague at first and I spent probably too long trying to figure out what 'reduction' meant before just asking.

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AI HintsAI Generated

Suggested Approach

Clarify the exact output required (max reduction or full series) and the event ordering (assume chronological). Then iterate through events, maintaining a running sum where recycled adds and waste subtracts, tracking the maximum if needed. Discuss time and space complexity, and consider edge cases like empty stream or ties.

Pro tip: Mention that if the stream is not sorted, you may need to sort by timestamp first, which adds O(n log n) time; if sorted, a single pass suffices. Also, note that the running series can be returned as a list of (timestamp, reduction) pairs.

1. Clarify requirements

Ask whether to return the maximum reduction or the full running series, and confirm the event ordering (e.g., chronological).

2. Define the reduction metric

Explain that reduction is computed as sum of recycled quantities minus sum of waste quantities, updated after each event.

3. Choose data structures

Use a simple running sum variable and, if returning the series, a list to store the running values; if finding max, a variable to track the maximum.

4. Process events

Iterate through events in order, update the running sum based on category, and update the max or append to the series as needed.

5. Analyze complexity and edge cases

State time complexity O(n) for sorted input, O(n log n) if sorting needed, and space O(1) for max or O(n) for series; discuss empty stream, negative reduction, and ties.

Key Points to Mention

  • Time complexity: O(n) for a single pass, O(n log n) if sorting is required.
  • Space complexity: O(1) for max reduction, O(n) for full series.
  • Handling unsorted streams: sort by timestamp first or use a min-heap if streaming.
  • Edge cases: empty stream, all waste (negative reduction), all recycled (positive reduction), ties for maximum.
  • Definition of reduction: recycled positive, waste negative.
  • Output format: if full series, include timestamps; if max, return the value.

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