Mine was on-campus placement, so CGPA, 10th and 12th marks did mattered. Keep everything above 75%, and you will be good to go. Round 1: Resume shortlisting Have an ATS score of 60 or above, even some people with as low as 40 ATS were selected but with extraordinary profile. Round 2: Aptitude (Easy, Pen-Paper) Quantitative aptitude, MS office, basic programming. It had 20 questions to be solved under 45min. 2-sets of question papers. Round 3: Programming (Easy, Pen-Paper) 3 DSA questions of LeetCode-Easy level questions. 1 Sorting question 1 Array/String manipulation 1 Star pattern question Tip: Explain code with suitable output. Round 4: Technical Interview (Medium, 1-on-1) They will ask you everything on your resume. They asked me to write OOPS implementations and SQL queries on paper. I mentioned ML/Data Science projects, internships and skills, so my interview revolved around those topics. Nothing in-depth was asked, just general overview about ML/Data Science. They asked me about my project tech stack, and how can I scale those projects. Round 5: Technical + HR Interview (Medium-Hard, 3 Panelists) They told us it was HR, but it was more or less technical. They brought out the programming round answer sheet and asked me to optimize the code, find out the time complexity and what other methods could be used instead of my code. Interview revolved around your approach, implementation and understanding logic, some were asked to write some code or explain architecture/diagram of topics related to your skill. I was asked to explain LSTM/RNN architecture (not draw) because I mentioned it in my resume, my friend was asked to draw DBMS schema. Tip: Draw diagram/architecture or explain in a visual form anywhere possible in any round, they will LOVE it!