AI isn’t making data science interviews easier.

I sit in hiring loops for data science/analytics roles, and I see a lot of discussion lately about AI “making interviews obsolete” or “making prep pointless.” From the interviewer side, that’s not what’s happening.

There’s a lot of posts about how you can easily generate a SQL query or even a full analysis plan using AI, but it only means we make interviews harder and more intentional, i.e. focusing more on how you think rather than whether you can come up with the correct/perfect answers.

Some concrete shifts I’ve seen mainly include SQL interviews getting a lot of follow-ups, like assumptions about the data or how you’d explain query limitations to a PM/the rest of the team.

For modeling questions, the focus is more on judgment. So don’t just practice answering which model you’d use, but also think about how to communicate constraints, failure modes, trade-offs, etc.

Essentially, don’t just rely on AI to generate answers. You still have to do the explaining and thinking yourself, and that requires deeper practice.

I’m curious though how data science/analytics candidates are experiencing this. Has anything changed with your interview experience in light of AI? Have you adapted your interview prep to accommodate this shift (if any)?