Round 1: Screening Round (On-Campus) The first round was an aptitude-based screening test conducted on campus. It primarily consisted of: Logical reasoning Basic mathematics Analytical problem-solving The questions were designed to evaluate problem-solving ability and logical thinking rather than deep technical knowledge. Round 2: Technical Assignment (AI/ML - Open Book) In the second round, I was given an open-book problem related to AI/ML. The task was to build a solution to detect fraudulent credit card transactions using machine learning algorithms. It tested understanding of concepts like: Classification problems Data preprocessing Model selection (e.g., Logistic Regression, Decision Trees, etc.) This round focused more on approach and reasoning rather than memorization. Round 3: Technical Interview (Deep Dive) This was a discussion-based round focused on the previous assignment. I was asked to explain: My approach to solving the fraud detection problem Choice of algorithms How I handled data imbalance and evaluation metrics Some additional questions were asked from: Basic programming concepts General technical knowledge The goal was to assess depth of understanding and clarity of thought. Round 4: HR Interview The final round was with HR, which included: Questions about background and experience Career goals and motivations Behavioral and situational questions This round focused on communication skills, cultural fit, and overall personality.