Summary
I interviewed for an MTS3 (UI) role at Nielsen, completing an LLD round to build a React Memory Game; despite successfully implementing the solution, the interviewer was disengaged, and I ultimately received a rejection.
Full Experience
I had an interview for an MTS3 (UI) role at Nielsen. The first round was dedicated to Low-Level Design (LLD). I was presented with a task to create a Memory Game using React. The requirements were to build an m x n grid of cards, each with a hidden value. Upon clicking a card, its value would be revealed. If two consecutive clicked cards had matching values, they were to be removed from the display; otherwise, they would flip back to hide their values. Additionally, the game needed to track the number of moves made. Although I successfully implemented the game, the interview itself was quite unusual. The interviewer shared the problem, then turned off his camera and remained largely disengaged throughout the session. He eventually asked me to share the code for his review later, which was a bit disconcerting. Overall, it wasn't a positive interview experience, and I later received a rejection.
Interview Questions (1)
Create a Memory Game in React. Given rows and columns, generate an m x n matrix of cards. Each card has a value. On click, a card reveals its value. If two revealed cards have matching values, remove them from the list. Otherwise, flip them back (hide their values). Also, keep track of the number of moves made.
Summary
I interviewed at Nielsen for the MTS-2 role in October 2025 and successfully received an offer after completing three rigorous rounds focused on Data Structures & Algorithms, System Design, and a technical-managerial discussion.
Full Experience
My interview journey at Nielsen for the MTS-2 role consisted of three rounds.
Round 1: DSA + Computer Science Fundamentals
This round started with a basic introduction. I was then presented with two Data Structures and Algorithms questions. Due to time constraints, we couldn't delve into Computer Science Fundamentals.Round 2: HLD + LLD (System Design)
This round focused on system design, where I was tasked with designing a movie ticket booking system, similar to BookMyShow. I began by clarifying requirements and then proceeded to outline a high-level flow for the system. I identified the necessary entities and their relationships, after which I drew a High-Level Design (HLD) of the overall system, incorporating services, an API gateway, and appropriate databases. We extensively discussed edge cases like concurrency and high traffic, and I explained various locking mechanisms (pessimistic, optimistic) along with database properties and different database options. In the remaining ten minutes, I quickly covered the Low-Level Design (LLD) of parts of the system.Round 3: Tech + Managerial (with Engineering Manager)
This final round involved an Engineering Manager. It started with a brief introduction from both sides. We then delved into an in-depth discussion about my previous company's role and projects. I drew an HLD of one of my past projects, explaining the technologies used and the approaches taken, including the rationale behind my choices and alternative options.Ultimately, I received an offer.
Interview Questions (3)
Given an array arr and a target value, find the count of distinct sets of {a,b,c,d} indices such that arr[a] + arr[b] + arr[c] + arr[d] = target. The indices a, b, c, d must be distinct.
Given an array arr, pick pairs of indices {i, j} for which 2*arr[i] <= arr[j]. Each index can only be part of one pair. Return the maximum number of such marked indices (total count of i and j chosen) in the array.
I was asked to design a movie ticket booking system similar to BookMyShow. This involved discussing basic requirements, outlining a high-level flow, identifying required entities and their relationships, and drawing an HLD of the overall system including services, API Gateway, and databases. We also covered edge cases such as concurrency and high traffic, discussing solutions like locking mechanisms (pessimistic, optimistic) and various database options and properties. Finally, I provided a quick Low-Level Design (LLD) for parts of the system.
Summary
I cold-emailed a recruiter and successfully secured an interview with Nielsen, progressing through three rounds covering Problem Solving/DSA, Low-Level Design, and Hiring Manager questions, ultimately receiving a job offer for the MTS - 2 role.
Full Experience
I cold-emailed a recruiter, and luckily, got a call from them after a few days.
The first round of the interview was scheduled for the following day.
Round 1 (1 hour) - Problem Solving / DSA
https://leetcode.com/problems/next-greater-element-i/https://leetcode.com/problems/binary-tree-maximum-path-sum/
Round 2 (1 hour) - LLD
Design a Task Management System that allows users to create, assign, update, and track tasks. The system should support multiple users, task priorities, due dates, and status tracking. Users should be able to categorize tasks, add comments, and receive notifications for task updates.Round 3 (1 hour) - Hiring Manager
The interviewer asked in-depth questions about my past projects, current work at my company, team leadership experiences, and various behavioral scenarios.I received positive feedback for this round the following day.
Verdict: Selected
Interview Questions (3)
The next greater element of some element x in an array is the first element to its right that is strictly greater than x. You are given two 0-indexed integer arrays nums1 and nums2 of unique elements, where nums1 is a subset of nums2. Find all the next greater elements for each of nums1's elements in the corresponding places of nums2. Return an integer array ans of length nums1.length where ans[i] is the next greater element for nums1[i]. If there is no next greater element for nums1[i] in nums2, then set ans[i] = -1.
A path in a binary tree is a sequence of nodes where each pair of adjacent nodes in the sequence has an edge connecting them. A node can only appear in the sequence at most once. Note that the path does not need to pass through the root. The path sum of a path is the sum of the node's values in the path. Given the root of a binary tree, return the maximum path sum of any non-empty path.
Design a Task Management System that allows users to create, assign, update, and track tasks. The system should support multiple users, task priorities, due dates, and status tracking. Users should be able to categorize tasks, add comments, and receive notifications for task updates.
Summary
I interviewed for the MTS-2 Full-Stack Developer role at Nielsen, which consisted of three comprehensive rounds covering diverse topics from data structures and system design to front-end and back-end development concepts. The director advised me to improve my React skills after the final round.
Full Experience
I recently interviewed for the MTS-2 Full-Stack Developer position at Nielsen, which was structured into three comprehensive rounds.
The first round was conducted by a BAR Raiser Platform (a 3rd party). It started with foundational computer science concepts, specifically delving into the internal workings of hashmaps and how collections behave in multithreaded environments. This was followed by a data structures and algorithms question on backtracking, specifically permutations, which I found on LeetCode. The interviewer then switched gears to front-end development, asking about React hooks and their practical use cases in a Photo Gallery App. We also discussed advanced UI/UX optimization techniques like skeleton loading, adaptive loading, and asset optimization for the same application.
The second round, lasting about 70-75 minutes, was with an MTS-2 level engineer. This round began with in-depth questions on multithreading and Kafka internals for roughly 15 minutes. A simple DSA question was posed, taking about 10-15 minutes. Following that, we moved into system design, where I was asked to discuss the High-Level Design (HLD) for an application similar to Myntra. This transitioned into a Low-Level Design (LLD) discussion for the 'Add to cart' functionality, covering both its back-end and front-end aspects, which consumed about half an hour. The round concluded with two SQL questions: a scenario-based question requiring the use of partitions, and another on LEFT JOIN queries.
Finally, the third round was with an Engineering Director and lasted approximately 45 minutes. This was primarily a behavioral and experience-based round. We discussed my previous projects, specifically doing an HLD walkthrough for one of them. A significant portion was dedicated to behavioral questions related to my project experiences and a discussion about the team I might be joining. The role itself is split 60%-40% between Back-End and Front-End development. Interestingly, the director advised me to improve my React skills.
Interview Questions (10)
Discuss the internal implementation details of a hashmap, including its data structure, collision resolution strategies, and performance characteristics.
Explain how collections work and behave in multithreaded environments, including potential issues like race conditions and common solutions for thread-safe collection access.
Discuss React Hooks, their principles, and demonstrate their practical application and benefits within the context of building a photo gallery application.
Explain and discuss methods like skeleton loading, adaptive loading, and asset optimization to improve the user experience and performance of a web application.
Discuss advanced concepts in multithreading and explain the internal architecture and working principles of Apache Kafka, including topics, partitions, producers, and consumers.
Design the high-level architecture for a large-scale e-commerce application similar to Myntra, considering scalability, availability, core functionalities (e.g., product catalog, user management, order processing), and relevant technologies.
Design the low-level architecture for the 'Add to Cart' functionality, covering both front-end (UI/UX, state management, API integration) and back-end (API endpoints, database interactions, business logic, error handling) implementations.
Solve a SQL scenario-based problem requiring the use of database partitioning for performance optimization or data management, explaining the rationale and implementation.
Write a SQL query demonstrating the use of a LEFT JOIN operation between two or more tables, explaining its behavior and use cases.