I applied online. The process took 2 weeks. I interviewed at Pattern in May 2025
Interview
Easy process. First round has a couple of Python questions and a SQL concept question. Short case study was also given. Second round was purely case study. The guy didn't even ask about my background or experience which was odd. Case study was easy - nothing complex but he probed on stuff which was like very basic and almost outdated - for example using rolling average for forecasting. Who does that anymore? Also he didn't have any answers for my questions which was again very lame. Recruiter sent a rejection email the next day. Overall, just got a feel that the team is not very technically advanced and seems to be highly male dominated with minimum diversity.
Interview questions [1]
Question 1
Bagging vs Boosting, overfitting dealing techniques, etc
It doesn’t feel like they are actually hiring. It seems they just want to show on LinkedIn that they are hiring. One of my contacts had a similar experience. Both of us appeared for interviews, and the interviews went very well, but we were told that they hired another person. Then, the same vacancy was reposted on LinkedIn the very next day. Maybe they don’t even have the budget in the first place. They were trying to hire senior-level candidates within a salary range of 10–15 LPA.
Interview questions [1]
Question 1
Normal around resume ml stuff doesn't seem anything different
I applied through a recruiter. The process took 4 weeks. I interviewed at Pattern in July 2025
Interview
First round was a general round checking python and SQL skills. The questions were apt to what generally encompasses data science domain and not random DSA questions. The interviewer then asked questions from resume checking fundamentals and verifying if you have actually worked on things you mention in resume.
2nd round was a very thorough discussion of 1.5 hours with a very vague case study. One is supposed to define the problem statement, data, modelling process, evaluation techniques etc. During this, the interviewer went into depth in a lot of ML modelling techniques and overall approach of solutioning.
Interview questions [2]
Question 1
Round 1:
The questions were SQL join conceptual and small implementation question followed by pandas questions to manipulate dataframe and calculate rolling average of lags.
Round 2:
Many questions and cross questions on your approach to the case study - why would you choose this data, what else could you do. Other what-if scenarios on this. In modelling, fundamental questions of how some model works - not superficial level answers but demanded thorough answers.