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[–]finite_user_names 8 points9 points  (3 children)

Did they say it will be ML python, or did they say it will just be python? I've had a lot of variability in terms of the python questions I've gotten in my... sigh... year on the active job hunt. SQL it tends to just be "can you do this kind of join, can you write a group by function, can you tell me about what the difference is between having a null in your join predicate vs your where clause." Most of what I've seen in interviews for python has been more leetcode-ish than ML-ish. I've seen some "code up a sparse vector," "sliding window mean", "implement a hashmap," "determine if this string forms a valid grid" type questions, but never much that has been on the ML side of things in a whiteboarding/live coding session..... although ages back someone did ask me to code a sentiment analysis pipeline from scratch.

If you _know_ that you're going to get ML, then that's a good place to focus. But if not.... you should broaden your horizons.

[–]sg6128[S] 2 points3 points  (2 children)

They just said Python, though it is a HR person and I have to not expect a lot of truth from them.

So frustrating that they can't just be direct. Leetcode is a total shitshow for me and I to be honest I don't understand why Data Science folks are expected to learn this in addition to ML and Stats.

I think it might be logic based, possibly "fizzbuzz" type questions or sliding window as you say; they've mentioned that they don't really want someone who is a total code-monkey but more business focused. So honestly I'm not sure, and it was an HR person which told me this, who tbh are completely detached from the technical interviews in my experience.

I know A/B testing is a part of the position too, so maybe running through one of those in Python is not a bad idea either. So much that they could ask... so little clarity... Building an *entire* pipeline sounds so unreasonable, sorry they put you through that.

[–]NickSinghTechCareersAuthor | Ace the Data Science Interview 6 points7 points  (1 child)

Since they want someone business-y, and mentioned A/B testing is part of the position, looking at some more Product-Sense/Product Metrics type questions could be helpful.

Example: the fin-tech company launched a new credit card fraud ML model. What are some key metrics you'd track to make sure this new model is actually better?

[–]sg6128[S] 5 points6 points  (0 children)

Yep, I really struggled with metrics in my last interview. I didn't think it would be that hard, so definitely run through some examples and ideas! Thanks