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Meesho Placement Papers 2025

This page is a working set of Meesho placement papers from 2025: from student reports questions, the 2025 online assessment pattern, and step-by-step solutions. Use it to see what Meesho actually asked in the latest cycle, how hard the rounds were, and which themes (DSA, system design, aptitude, or role-specific topics) mattered most. Practice the problems below under timed conditions, then cross-check with the interview and preparation guides if you are targeting an upcoming Meesho drive.

Section Questions Time Difficulty Focus Areas
Coding Problems 2-3 60-90 min Medium-Hard Arrays, trees, graphs, DP

Total: 2-3 problems, 60-90 minutes
Platform: HackerRank or similar
Languages Allowed: Python, Java, JavaScript
Success Rate: ~15-20% cleared OA and advanced to interviews

Meesho Placement Papers 2025 - actual questions & solutions

Section titled “Meesho Placement Papers 2025 - actual questions & solutions”

This section contains practice questions styled on Meesho placement papers 2025 (recent-cycle pattern), with worked solutions. Use them as timed sectional drills - from student reports drives vary by college and role, so treat this as a high-signal practice bank, not an official paper dump.

Show solution

Problem Statement: Rotate the array to the right by k steps.

Example:

Input: [1,2,3,4,5,6,7], k = 3
Output: [5,6,7,1,2,3,4]

Solution (Java):

public void rotate(int[] nums, int k) {
k %= nums.length;
reverse(nums, 0, nums.length - 1);
reverse(nums, 0, k - 1);
reverse(nums, k, nums.length - 1);
}
void reverse(int[] a, int l, int r) {
while (l < r) { int t = a[l]; a[l++] = a[r]; a[r--] = t; }
}

Time Complexity: O(n)
Space Complexity: O(1)

Show solution

Problem Statement: Return the first non-repeating character in a string, or ‘_’ if none.

Example:

Input: "swiss"
Output: 'w'

Solution (Java):

public char firstUnique(String s) {
int[] freq = new int[256];
for (char c : s.toCharArray()) freq[c]++;
for (char c : s.toCharArray()) if (freq[c] == 1) return c;
return '_';
}

Time Complexity: O(n)
Space Complexity: O(1)

Show solution

Problem Statement: Return the level-order traversal of a binary tree.

Example:

Input: [3,9,20,null,null,15,7]
Output: [[3],[9,20],[15,7]]

Solution (Java):

public List<List<Integer>> levelOrder(TreeNode root) {
List<List<Integer>> res = new ArrayList<>();
if (root == null) return res;
Queue<TreeNode> q = new ArrayDeque<>();
q.add(root);
while (!q.isEmpty()) {
int sz = q.size();
List<Integer> level = new ArrayList<>();
for (int i = 0; i < sz; i++) {
TreeNode n = q.poll();
level.add(n.val);
if (n.left != null) q.add(n.left);
if (n.right != null) q.add(n.right);
}
res.add(level);
}
return res;
}

Time Complexity: O(n)
Space Complexity: O(n)

Show solution

Problem Statement: You can climb 1 or 2 steps. How many distinct ways to climb n stairs?

Example:

Input: n = 4
Output: 5

Solution (Java):

public int climbStairs(int n) {
if (n <= 2) return n;
int a = 1, b = 2;
for (int i = 3; i <= n; i++) {
int c = a + b; a = b; b = c;
}
return b;
}

Time Complexity: O(n)
Space Complexity: O(1)

Show solution

Problem Statement: Given an array of integers and a target, return indices of two numbers that add up to target.

Example:

Input: nums = [2, 7, 11, 15], target = 9
Output: [0, 1]

Solution (Java):

public int[] twoSum(int[] nums, int target) {
Map<Integer, Integer> map = new HashMap<>();
for (int i = 0; i < nums.length; i++) {
int need = target - nums[i];
if (map.containsKey(need)) return new int[]{map.get(need), i};
map.put(nums[i], i);
}
return new int[]{};
}

Time Complexity: O(n)
Space Complexity: O(n)

Show solution

Problem Statement: Return true if the linked list has a cycle.

Example:

Input: 3→2→0→-4→(back to 2)
Output: true

Solution (Java):

public boolean hasCycle(ListNode head) {
ListNode slow = head, fast = head;
while (fast != null && fast.next != null) {
slow = slow.next;
fast = fast.next.next;
if (slow == fast) return true;
}
return false;
}

Time Complexity: O(n)
Space Complexity: O(1)

Show solution

Problem Statement: Merge two sorted linked lists and return a new sorted list.

Example:

Input: 1→2→4 , 1→3→4
Output: 1→1→2→3→4→4

Solution (Java):

public ListNode mergeTwoLists(ListNode a, ListNode b) {
ListNode dummy = new ListNode(0), cur = dummy;
while (a != null && b != null) {
if (a.val <= b.val) { cur.next = a; a = a.next; }
else { cur.next = b; b = b.next; }
cur = cur.next;
}
cur.next = (a != null) ? a : b;
return dummy.next;
}

Time Complexity: O(n + m)
Space Complexity: O(1)

Q8: In OOP, hiding internal details and showing only essential features is called?

Solution:

This is the definition of Encapsulation (often paired with abstraction in interviews).

Answer: Encapsulation

Q9: Worst-case time complexity of quicksort is?

Solution:

Unbalanced partitions (already sorted with bad pivot) → O(n²).

Answer: O(n²)

Q10: Which protocol is connection-oriented at the transport layer?

Solution:

TCP is connection-oriented; UDP is connectionless.

Answer: TCP

Q11: Which normal form removes transitive dependency?

Solution:

1NF: atomic values. 2NF: no partial dependency. 3NF: no transitive dependency.

Answer: 3NF

Key insights from 2025 Meesho Online Assessment

Section titled “Key insights from 2025 Meesho Online Assessment”
  1. Coding Section is Critical: Must solve 2-3 coding problems correctly to advance
  2. DSA Focus: Strong emphasis on arrays, strings, trees, graphs, and dynamic programming
  3. Time Management: 2-3 problems in 60-90 minutes requires excellent speed and accuracy
  4. E-commerce Focus: Problems often relate to e-commerce systems, product recommendations, social commerce, AI-powered features
  5. System Design: Asked for SDE-1/2 roles, e-commerce system design for social commerce roles
  6. Success Rate: Only 15-20% cleared OA and advanced to interviews
  7. Platform: HackerRank or Meesho’s internal platform
  8. Focus Areas: Arrays, trees, graphs, dynamic programming, e-commerce systems, social commerce, AI/ML
  9. Enhanced Emphasis: Optimal solutions, AI-powered recommendations, and cloud-native e-commerce platforms

Based on recent candidate experiences from 2025 Meesho interviews:

2025 Interview Process:

  1. Online Assessment (60-90 minutes): 2-3 coding problems
  2. Technical Phone Screen (45-60 minutes): Coding problems, algorithm discussions, e-commerce concepts, AI/ML
  3. Onsite/Virtual Interviews (4-5 rounds, 45-60 minutes each):
  • Coding rounds (2-3): Algorithms, data structures, problem-solving
  • System Design rounds: AI-powered e-commerce platforms, social commerce systems, product recommendations, cloud-native architecture
  • Behavioral rounds: Problem-solving approach, innovation, impact, AI/ML passion

2025 Interview Trends:

  • Increased emphasis on AI-powered recommendations and cloud-native e-commerce platforms
  • More focus on optimal solutions and social commerce system design
  • Enhanced behavioral questions about innovation and impact
  • Questions about AI/ML applications in e-commerce and social commerce

Common 2025 Interview Topics:

  • Coding: Arrays, strings, trees, graphs, dynamic programming, e-commerce algorithms
  • System Design: AI-powered e-commerce platforms, social commerce systems, product recommendations, cloud-native architecture
  • Behavioral: Problem-solving, innovation, teamwork, impact, AI/ML passion
  • Meesho Technologies: Social commerce, AI-powered features, e-commerce platforms, product recommendations, cloud-native platforms

Success Tips:

  • Strong coding performance is essential - solve problems optimally
  • Understand e-commerce, AI-powered social commerce, and cloud-native e-commerce systems
  • Practice system design for AI-powered e-commerce platforms and social commerce systems
  • Prepare examples demonstrating innovation and problem-solving
  • Learn Meesho’s products, AI features, and social commerce model
  • Practice explaining your thought process clearly

For detailed interview experiences from 2025, visit Meesho Interview Experience page.

  1. Master Coding Fundamentals: Focus on solving 2-3 coding problems correctly - arrays, trees, graphs, DP
  2. E-commerce Expertise: Strong understanding of AI-powered e-commerce systems, social commerce, product recommendations
  3. Practice Previous Year Papers: Solve Meesho OA papers from 2020-2025 to understand evolving patterns
  4. Time Management: Practice completing 2-3 coding problems in 60-90 minutes
  5. LeetCode Practice: Solve 200+ LeetCode problems focusing on arrays, strings, trees, graphs (medium-hard difficulty)
  6. E-commerce Focus: Practice problems related to e-commerce systems, social commerce, AI/ML in e-commerce
  7. System Design Mastery: Learn AI-powered e-commerce platform design, social commerce systems, product recommendations, cloud-native architecture
  8. Meesho Technologies: Learn social commerce, AI-powered features, e-commerce platforms, product recommendations, cloud-native platforms
  9. Behavioral Preparation: Prepare examples using STAR format - innovation, problem-solving, AI/ML passion
  10. Mock Tests: Take timed practice tests to improve speed and accuracy
  11. AI/ML in E-commerce: Understand AI/ML applications in e-commerce and social commerce

Flipkart · Zomato · Swiggy · Paytm · Phonepe · Razorpay


Practice 2025 papers to stay updated with latest patterns and prepare effectively!