Array Questions at Myntra: What to Expect

Array questions dominate Myntra's technical interviews, making up 17 of their 24 most frequently asked problems. This isn't a coincidence. Myntra's core business—an e-commerce platform handling millions of product listings, user carts, recommendations, and real-time inventory—relies heavily on efficient data organization and retrieval. Arrays are the fundamental structure for sequences of product IDs, price lists, user behavior logs, and image data for catalogs. Mastering array manipulation is not just about solving an interview problem; it's about demonstrating you can handle the data flows that power a large-scale fashion and lifestyle platform.

What to Expect — Types of Problems

Myntra's array questions focus on practical application, testing your ability to transform and analyze data efficiently. You can expect these core categories:

1. Sorting and Searching: Fundamental to organizing product listings (by price, popularity) and finding items. Expect variations on binary search and custom sorting logic.
2. Subarray Problems: Crucial for analyzing contiguous data segments, like finding the best-selling streak of products or calculating metrics over a user session window. Problems often involve sums, products, or specific conditions.
3. Two-Pointer Technique: A favorite for optimizing operations on sorted arrays or finding pairs, mirroring tasks like matching complementary fashion items or de-duplicating entries.
4. Prefix Sum or Running Calculations: Essential for answering rapid range queries, such as calculating total sales in a time period or average ratings, which are common dashboard features.
5. In-Place Array Modification: Tests your skill at manipulating data within memory constraints, akin to updating inventory levels or reorganizing product feeds without extra space.

The problems often combine these patterns and require an optimal O(n) or O(n log n) solution.

How to Prepare — Study Tips with One Code Example

Focus on pattern recognition, not memorization. Understand the underlying technique for each problem type. Practice explaining your reasoning aloud as you code. For Myntra, always clarify input assumptions (e.g., is the array sorted? can it contain negatives?) as this reflects real-world data handling.

A key pattern is the Sliding Window for subarray problems. Here is a template for finding the maximum sum of any contiguous subarray of size k:

def max_sum_subarray(arr, k):
    if len(arr) < k:
        return None
    window_sum = sum(arr[:k])
    max_sum = window_sum

    for i in range(k, len(arr)):
        window_sum = window_sum - arr[i - k] + arr[i]
        max_sum = max(max_sum, window_sum)
    return max_sum

Recommended Practice Order

Build competence progressively:

1. Start with fundamentals: binary search, two-pointer, and basic in-place operations.
2. Move to core patterns: sliding window (fixed and variable size) and prefix sum applications.
3. Tackle combination problems that merge techniques, like sorting followed by two-pointer search.
4. Finally, solve Myntra's specific tagged problems to familiarize yourself with their question style and difficulty.

Practice Array at Myntra