Ramp·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say

Apr 2026

Summary

Ramp SWE interview with a stock trading problem that looks like the classic buy-low-sell-high puzzle but has a few wrinkles around unsorted dates and multiple symbols. Pretty clean problem overall, though the edge cases around same-date trades and symbols with only one record are the kind of thing that'll trip you up if you're not careful.

Questions Asked (1)

Given an unsorted log of stock trades, each with a date, ticker symbol, and price, find the maximum profit from a single buy-then-sell transaction where the sell date must be strictly later than the buy date and both trades share the same symbol. Return 0 if no profitable transaction exists.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

My first instinct was to just sort everything by date and run the standard min-so-far sweep, but then I realized you have to track each symbol separately since you can't buy AAPL and sell GOOG.

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AI HintsAI Generated

Suggested Approach

Clarify that the problem reduces to finding, for each symbol, the maximum difference between a later sell price and an earlier buy price, then take the global maximum. Process the log chronologically while maintaining the minimum price seen so far per symbol, updating the best profit when a higher price appears. Return 0 if no positive profit is found.

Pro tip: Mention that the log is unsorted, so you must sort by date first (or use a per-symbol min-price map if dates are already comparable). Also note that you should handle multiple symbols independently and avoid mixing them, which is a common pitfall.

1. Clarify requirements and edge cases

Confirm that each transaction is a single buy and sell of the same symbol, sell strictly after buy, and that profit is sell price minus buy price. Ask about input size, date format, and whether multiple trades on the same date are allowed.

2. Sort or group by symbol and date

Since the log is unsorted, sort by date (and symbol) or group trades by symbol and sort each group by date. This ensures chronological processing per symbol.

3. Track minimum price and maximum profit per symbol

Iterate through the sorted trades, maintaining the minimum buy price seen so far for each symbol. For each trade, compute the potential profit if sold at the current price and update the global maximum profit.

4. Return the result

After processing all trades, return the maximum profit found, or 0 if no profitable transaction exists.

Key Points to Mention

Time complexity: O(n log n) due to sorting, or O(n) if dates are already sorted or can be bucketed; space complexity O(n) for grouping or O(k) for per-symbol state.
Handling multiple symbols: process each symbol independently to avoid invalid cross-symbol transactions.
Strictly later sell date: ensure the sell date is after the buy date, not equal; this affects sorting and comparison.
Edge cases: no profitable transaction (return 0), single trade, all prices decreasing, duplicate dates.
Alternative approach: for each symbol, find max profit using a single pass after sorting, similar to the classic 'best time to buy and sell stock' problem.
Trade-offs: sorting may be avoided if we can use a hash map of min price per symbol and process in any order, but we must ensure chronological order per symbol.

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