The interview process began with a thorough resume review, where interviewers delved into my past experiences and projects in detail. This was followed by technical rounds assessing relevant mathematics and statistics knowledge, including probability, linear algebra, and statistical inference concepts. There were also questions on Python programming, covering data structures, algorithms, libraries like NumPy and Pandas, and best practices. The process included live coding tests with practical problems to solve in real-time, focusing on clean, efficient code. Overall, it was rigorous but fair, emphasizing problem-solving skills.