It was a systematic interview process: Round 1: DoSelect coding round - All relevant questions - including AI/ML-based MCQs and ML Modelling-based questions. The time constraint was the hardest part of this round, otherwise, questions were of average difficulty if you know the fundamentals. Round 2: Technical (Senior Data Scientist) - Starting from project experience, it covered major important ML/DL concepts and questions from the skillset mentioned in the Resume. Round 3: Technical + Managerial (Lend Data Scientist) - It was somewhat similar to the previous round, more focused on the Techanalities of my project in detail. Why? and Why not? questions from my previous work and the use of various ML/DL concepts and their alternatives. The interviewer was also interested in knowing my role and responsibilities in the current organization. Round 4: Technical + Managerial (VP) - It was focused more on the kind of projects I worked on and my contributions (in detail), career objective, and aspirations, it also delves into my skillset and target in terms of learning. Round 5: Managerial (Manager) - The interviewer was interested in knowing the vastness of all my previous projects and my role in those. I was being asked about my understanding of various Data Science concepts in detail (i.e. NLP, Timeseries Analysis, Mathematical optimization, etc.). I was asked a basic program logic even in this round. Round 6: HR: Duration was ~30 mins, and I was asked about reasons behind job change and aspiration. HR asked for depth in my answers which eventually helped her getting many other questions answered. I felt all rounds were elimination rounds, including the final HR round. During this entire process, the support and details provided by my TA contact person Jesvin were really helpful. It made me create a rough plan and decide on the depth of my answers. I received a positive response and an offer letter in the next 4 days. It was challenging and an amazing experience.