Tessian Data Scientist Interview Questions
& Process

After applying online and a CV screen, I was given a quick Python challenge and an open-ended Data Science challenge. Then, I had an interview with the Head of Data Science where we mostly discussed my response to the DS challenge and my previous projects. It was a lot more relaxed and informative than the typical hour-long grilling sessions you'd expect from tech companies.

This was for a Lead Data Scientist-NLP role. After all rounds went well, I was rejected, with the reason being high competitiveness. It felt like they were gathering ideas rather than actively hiring, and the chances of getting in seem slim. It's a competitive process. The first round was an easy coding challenge on prefix/infix expressions on a coding platform. This was followed by a short 30-minute introductory call to discuss background and interests. Then, there was a 2-hour problem-solving session. This round involved discussing how to build a system for brand impersonation detection, including identifying issues with sample data, outlining a high-level solution flow, and discussing various nuances of the problem. I think the time allocation for the solution flow diagram was a bit tight, as expecting a finished diagram in 10 minutes isn't ideal and doesn't allow for unconstrained thinking. Despite feeling I answered well, the feedback was just that it was highly competitive, and the role has been advertised for months, suggesting they might have interviewed many candidates without hiring.

Had a Hacker rank interview which I passed. Then had a technical role discussion, also passed. There was a technical interview, but they rescheduled it multiple times. Finally, they informed me the position was filled.