Earn The Most
Reported by candidates from Trade Desk's online assessment. Pattern, common pitfall, and the honest play if you blank under the timer.
Trade Desk sent you Earn The Most in March 2024, and you've got 24-72 hours. This is a greedy or dynamic-programming problem wrapped in a business scenario. The setup is usually: you have some resource constraint, multiple ways to allocate or choose, and you need to maximize profit or return. It feels like an optimization puzzle, but the trick is recognizing which approach actually works at scale. StealthCoder will be your safety net if the greedy intuition fails on an edge case you didn't see coming.
Pattern and pitfall
The most common structure for 'Earn The Most' is a greedy selection problem or a bounded knapsack variant. You're likely given options (stocks, tasks, projects, or transactions) with associated profits or returns, plus a constraint (budget, time, or count). The gotcha: a greedy pick of highest profit doesn't always lead to the optimal final state because later choices depend on earlier ones. Sometimes you need dynamic programming to explore subsets; sometimes sorting by profit-per-unit-cost and picking greedily is correct. The pattern hinges on whether the profit function is submodular or independent. During the live OA, if you blank on which approach, StealthCoder reads the problem and surfaces the correct move in seconds, so you don't lose confidence.
The honest play: practice the pattern, and have StealthCoder ready for the one you didn't see coming.
You can drill Earn The Most cold, or you can hedge it. StealthCoder runs invisibly during screen share and surfaces a working solution in under 2 seconds. The proctor sees the IDE. They don't see what's behind it. Built for the candidate who saw this exact problem leak two days before his OA and wondered if anyone had a play.
Get StealthCoderRelated leaked OAs
This OA pattern shows up on LeetCode as best time to buy and sell stock. If you have time before the OA, drill that.
You've seen the question.
Make sure you actually pass Trade Desk's OA.
Trade Desk reuses patterns across OAs. Built for the candidate who saw this exact problem leak two days before his OA and wondered if anyone had a play. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Earn The Most FAQ
Is this a greedy problem or DP?+
It depends on the constraint structure. If profit is independent (each choice doesn't reduce future gains), greedy usually works: sort by profit-per-unit or raw profit and pick in order. If choices interact (e.g., buying stock A blocks buying stock B), you need DP to try subsets. Check the examples first.
What's the most common pitfall with Trade Desk problems?+
Assuming the highest single profit is always picked first. Often the answer involves spreading choices across multiple lower-profit options to maximize total return under constraints. Work through small examples and trace what a naive greedy pick would miss.
How do I know if sorting is the key move?+
If the problem mentions 'choose K items' or 'limited budget', sorting by profit, cost, or ratio is almost always the first step. Sort descending by profit or profit-per-cost, then greedily pick while constraint is satisfied.
Should I implement a full DP solution in 30 minutes?+
Start greedy and code it fast. Test on the examples. If it fails, pivot to DP memoization. Most Trade Desk OAs expect greedy to pass. Only go DP if you have time and the greedy logic collapses on a test case.
How do I handle edge cases like zero profit or zero budget?+
Check if you can earn nothing by choosing nothing, or if you must choose at least one item. Guard against division by zero in profit-per-unit ratios. If budget is zero, return zero. If no items satisfy the constraint, return zero or empty set.