The comprehensive evaluation process consisted of two rigorous technical interview rounds, meticulously designed to assess candidates' depth of knowledge in machine learning and their adeptness in analytical problem-solving. These interviews aimed to thoroughly examine each candidate's qualifications and suitability for the role, scrutinizing their ability to apply machine learning concepts effectively and tackle complex puzzles with innovative solutions. Through these rounds, the interviewers sought not only to gauge the candidates' technical competence but also their creativity, adaptability, and critical thinking skills. The combination of machine learning expertise and puzzle-solving acumen served as a holistic assessment, ensuring that the chosen candidate would be well-equipped to excel in the multifaceted challenges of the role.

The interview process consists of 2 rounds. Both rounds involve questions from projects mentioned in the resume, SQL, machine learning fundamentals, business case studies, guesstimates, and logical puzzles. The interviews didn't go too much into the nitty-gritty details of projects but only asked for a high-level overview.