The interview began with an online assessment that included 8 multiple-choice questions covering statistics and machine learning theory concepts, such as probability, hypothesis testing, bias-variance trade-off, and model evaluation. After that, there were 3 coding tasks designed as a sequence: each step required building part of a machine learning model, with the next question continuing from the previous output. For example, the first task involved data preprocessing, the second focused on model training, and the final one on evaluation and interpretation. This format tested both theoretical knowledge and applied coding skills in a progressive way.