When I went through the process, it started with the Online Assessment (OA), which tested my SQL, probability, statistics, and a couple of medium-level coding questions. Once I cleared that, the first technical round (Tech R1) focused on core data science concepts — I was asked to write SQL queries, explain hypothesis testing, and solve a coding exercise. The second technical round (Tech R2) was more applied: I had to walk through an end-to-end ML project, discuss feature engineering, and solve a business case around predictive modeling. The third technical round (Tech R3) tested both technical and behavioral skills. I got questions on A/B testing design, dealing with biased data, and also a lot of Amazon Leadership Principles, where I had to give structured answers using STAR. Finally, the HR/Bar Raiser round was more about culture fit and motivation, with some situational judgment questions around leadership principles again. Overall, I felt the process was structured to evaluate not just technical strength in statistics, ML, and SQL, but also problem-solving, business intuition, and alignment with Amazon’s culture.