Fractal Data Scientist Interview Questions
& Process

The interview process was super organized, big thanks to Jesvin Varghese, my recruiting manager. He was upfront about the job, the culture, and even gave prep tips. He managed to schedule everything really fast, even with my short notice period. The interviews had 3 parts. First was a breadth assessment covering Data Science, including ML, DL, and GenAI, with some coding. It was pretty easy to moderate. Then, a deep dive technical round focusing on NLP and AI, covering things like sentence transformers, RAG, and transformers. This was tougher. Finally, a culture fit round to see if I'd fit in, which was a relaxed chat about my work style and values. It felt more like a conversation than an interview.

HR called me first, asked about my qualifications and experience. Then, they set up a technical interview with a senior data scientist. About a week or two later, I got an email with a link to a test. The test was kinda hard, with some MCQs and a modeling problem. Two weeks after that, I got a call about scheduling a third-round techno-managerial interview. I haven't heard back from HR since then.

So the interview process for the Data Scientist role here at Fractal started with a technical test, which had 13 questions in total, 11 were multiple choice and 2 were machine learning problems. Then there was Round 1 where they checked my basic understanding of ML, asked for a deep dive into my previous projects, and also a live coding session. Round 2 involved more questions on basic ML understanding and some business problems to see my approach. Finally, there was a discussion with HR about why I'm interested in Fractal, my long-term and short-term goals, and my expected CTC.