During the recent recruitment drive, I had the opportunity to participate in multiple stages of the selection process, with a strong focus on assessing problem-solving skills through Data Structures and Algorithms (DSA). The drive was structured to evaluate not only technical competence but also logical reasoning, time management, and the ability to handle coding challenges under pressure. The DSA round began with the interviewer introducing themselves and giving me an overview of the expectations. They clarified that the problems would be focused on algorithmic thinking, efficiency, and code correctness, and that I would need to discuss my approach before jumping into implementation. This made it clear that they valued clear communication and structured problem-solving in addition to coding ability. The first problem tested fundamental array manipulation and required me to optimize my solution to run in linear time. I started by explaining the brute-force approach and then refined it using a more optimal algorithm, justifying the time and space complexity trade-offs. The interviewer appreciated the way I walked through my thought process. The second problem was more advanced and touched on graph traversal concepts. I was asked to find an efficient way to detect a certain pattern within a dataset, which required applying BFS/DFS concepts. I discussed possible approaches, compared their complexities, and then implemented the most efficient one.