Product Madness Data Scientist Interview Questions
& Process

This was a long and drawn out process with 7 interviews. Why do they need 7 interviews to determine if you are a viable candidate? Interviews included multiple technical (python, sql) and statistical (probability theory, statistical analysis, hypothesis testing) assessments after an initial introductory call. I was also told that I would be attending a final round interview with the hiring manager and it would be a casual chat (after 6 rounds of interviews). Turns out it was a ML modelling interview, where they asked broad and frankly stupid questions e.g., "imagine what data we have, now how would you use this data without actually looking at it". And, for the cherry on top, there was still another interview after that. It's crazy this company expects 10+ hours of your time for an interview process as if they are FAANG company, yet their recruitment process is a mess (although most of the employees I met were friendly and knew what they were talking about), and they don't offer anywhere near the same level of compensation. I would recommend you don't apply for this company, unless you want many hours of your precious time wasted for average compensation, or more likely, the feeling of being ghosted after giving so much of your time.

First, a recruiter reviewed my CV for relevancy. Then, I had a Skype interview where I discussed technical aspects of my background. This was a friendly chat that gave a good vibe of the company and people. Next was an online coding test with SQL and an algorithm problem; it was a standard coding challenge to pass. Surprisingly, no data science was involved. The final stage was an onsite interview with the group head and another team member. It started with a case study, involving unstructured questions about a scenario with follow-ups. Some questions were ambiguous, and feedback wasn't always provided. Then, we moved to a whiteboard for a SQL question. The lack of clear feedback and direction made me freeze a bit. Despite this, the team members were friendly and gave a good impression. We briefly touched on other technical work I'd done, but they weren't familiar with it. No general data science or management questions were asked, nor was my background in those areas explored. It seems the group is mainly focused on database analysis and dashboards, hence the emphasis on coding and SQL. It's unclear if they truly need broader data science expertise. I didn't get any feedback afterwards.

After an initial HR screening, candidates need to complete a take-home test involving SQL and Python. This is followed by a three-round interview process. The first technical round focuses on Python coding, covering programming fundamentals, Data Science ML techniques, and problem-solving. The final interview is with the Data Science director and assesses statistics and logical thinking skills. Unfortunately, they decided to move forward with another candidate after the last stage. If you have experience with various data science tasks, it shouldn't be too difficult to pass, though luck can play a part sometimes. Overall, I was pleased with the entire interview experience and the company culture seems great.