Greedy Questions at Coupang: What to Expect

Greedy algorithms are a significant part of Coupang's technical interview, representing about 11% of their problem catalog. For a company optimizing massive logistics networks, delivery routes, and inventory allocation, greedy strategies—making the locally optimal choice at each step—are not just an academic exercise but a practical tool for real-time decision-making. Mastering these questions demonstrates you can think about efficiency and incremental optimization, which is core to Coupang's operations.

What to Expect — Types of Problems

Coupang's greedy questions typically fall into a few predictable categories. You won't see overly complex mathematical proofs; instead, expect applied problems where a sorted order or a simple rule leads to the solution.

• Interval Scheduling: Problems involving meeting rooms, tasks, or time intervals where you need to select the maximum number of non-overlapping activities. This is a classic greedy pattern.
• Assignment & Partitioning: Distributing resources or splitting groups in a way that minimizes cost or maximizes fairness (e.g., load balancing, dividing array into subsets).
• Coin Change / Greedy Choice: Problems where the standard greedy coin algorithm works (e.g., using the largest denomination first). Be cautious, as this only applies to specific coin systems.
• String Manipulation: Constructing lexicographically smallest/largest strings or palindromes by making optimal character-by-character choices.

The key is recognizing the problem allows for a greedy approach. The interviewer will often want to hear your reasoning: "Why is it safe to take this item first?"

How to Prepare — Study Tips with One Code Example

First, solidify the core principle: a greedy algorithm builds a solution piece by piece, always choosing the next piece that offers the most immediate benefit. To prepare:

1. Learn the canonical patterns: Interval scheduling, task scheduling, and greedy coin change are fundamental. Understand why sorting is often the first step.
2. Prove it to yourself: Before coding, verbally justify why the greedy choice is optimal. This is crucial for the interview discussion.
3. Start with sorting: If a problem involves "maximum number," "minimum cost," or "optimal arrangement," try sorting the data first. The solution often emerges from processing the sorted order.

A perfect example is the "Maximum Number of Events You Can Attend" type problem. The greedy strategy is to always attend the event that ends the earliest, freeing up your time for more events later.

def max_events(events):
    # events: list of [startDay, endDay]
    events.sort(key=lambda x: x[1])  # Sort by end day
    attended = set()
    for start, end in events:
        # Attend on the first available day within the event's range
        for day in range(start, end + 1):
            if day not in attended:
                attended.add(day)
                break
    return len(attended)

Recommended Practice Order

Tackle problems in this order to build confidence:

1. Classic Foundations: Start with simple interval scheduling (Meeting Rooms, Non-overlapping Intervals).
2. Greedy on Sorted Arrays: Move to problems like Assign Cookies or Minimum Number of Arrows to Burst Balloons.
3. More Complex Selection: Try Task Scheduler or problems requiring a priority queue (heap) to manage the greedy choice efficiently.
4. Coupang-Specific: Finally, practice the actual greedy problems tagged for Coupang on CodeJeet to familiarize yourself with their style and difficulty.

Practice Greedy at Coupang