How important are LeetCode-style data structure/algorithm questions for data science interviews?

Question

I am a new graduate working as a data scientist at a mid-sized company. I'm wondering about the importance of LeetCode for data science interviews. I'm comfortable with SQL and can handle hard-level SQL problems, but I struggle with medium and hard-level coding questions (non-sql/algorithm style) on LeetCode. On the flip side, I am very comfortable with ML and DL algorithms. Should I focus more on building ML/DL projects or on mastering medium and hard-level LeetCode problems?

Alex Chiou · Accepted Answer

LeetCode/DSA-style problems are terrible enough already for software engineers - I imagine it's even worse for Data Scientists. I don't think you should spend significant time studying LeetCode (especially the hard-label questions) unless you are 90%+ sure an upcoming interview will have that kind of question.

I've talked with data scientists a little about their interviews and I've talked with data engineers even more: The consensus seems to be that LeetCode isn't nearly as common for them as it is for SWE while SQL very much is (which makes sense as it's what data folks actually do).

This economy is also one of the absolute worst to blindly grind LeetCode in as 80% of Big Tech companies are doing hiring freeze.

Check out the resources here as well: [Taro Top 10] Effective Interview Prep

How important are LeetCode-style data structure/algorithm questions for data science interviews?

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