Greedy Questions at Wayfair: What to Expect

Greedy algorithms are a small but critical part of Wayfair’s technical interview process. While only 2 out of their 21 common questions are explicitly tagged as Greedy, these problems test a candidate’s ability to make a series of locally optimal choices to arrive at a globally optimal solution. This mirrors real-world engineering decisions at Wayfair, such as optimizing delivery routes, warehouse slot allocation, or resource scheduling for their massive e-commerce platform. Successfully solving a Greedy question demonstrates strong problem decomposition and logical reasoning—key traits for building efficient systems at scale.

What to Expect — Types of Problems

Wayfair’s Greedy questions typically fall into two categories: interval-based problems and assignment/ordering problems.

Interval Problems involve scheduling or selecting non-overlapping intervals. You might be asked to find the minimum number of rooms needed for meetings or the maximum number of non-overlapping tasks. The core skill is sorting intervals and making greedy choices about which to keep or discard.

Assignment/Ordering Problems focus on arranging elements to minimize cost or maximize output. Examples include assigning tasks to workers for minimum completion time or rearranging a sequence to satisfy specific constraints with minimal swaps. These questions assess your ability to see the optimal structural pattern in seemingly complex scenarios.

The difficulty is usually medium. You won’t encounter highly obscure Greedy puzzles; instead, expect recognizable patterns applied to a business-like context, such as optimizing logistics or layouts.

How to Prepare — Study Tips with One Code Example

Mastering Greedy algorithms requires pattern recognition, not memorization. Follow these steps:

1. Learn the Core Principles: Understand that a Greedy algorithm builds a solution piece by piece, always choosing the next piece that offers the most immediate benefit. A valid Greedy approach requires optimal substructure and the greedy-choice property.
2. Practice Classic Problems: Build intuition by solving standards like "Meeting Rooms," "Task Scheduler," or "Fractional Knapsack."
3. Prove Your Approach: Be prepared to justify why your greedy choice works. Interviewers often ask for reasoning.

A key pattern is the "Earliest End Time" strategy for interval scheduling. To maximize the number of non-overlapping intervals, you sort by end time and greedily pick the next non-conflicting interval that ends the earliest.

def max_non_overlapping_intervals(intervals):
    # Sort intervals by their end time
    intervals.sort(key=lambda x: x[1])
    count = 0
    last_end = float('-inf')

    for start, end in intervals:
        if start >= last_end:  # No overlap
            count += 1
            last_end = end
    return count

Recommended Practice Order

1. Start with foundational problems: "Meeting Rooms" (LeetCode 252) and "Merge Intervals" (LeetCode 56) to understand interval manipulation.
2. Move to classic greedy choices: "Non-overlapping Intervals" (LeetCode 435) and "Task Scheduler" (LeetCode 621).
3. Tackle assignment problems: "Assign Cookies" (LeetCode 455) and "Minimum Number of Arrows to Burst Balloons" (LeetCode 452).
4. Finally, simulate the interview by solving Wayfair’s tagged Greedy questions under timed conditions.

Practice Greedy at Wayfair