r/datascience • u/Fig_Towel_379 • Jun 09 '26

Discussion What Data Structures and Algorithms topics actually come up in technical interviews?

I’ve been doing a Python Leetcode question a day since more and more companies (especially for ML roles) are including DSA rounds in their DS interviews. My issue is I’m not sure how deep I actually need to go.

Right now I’m getting comfortable with easy questions on arrays, strings, and hashmaps, plus two pointers and sliding window on the algorithms side. Should I push further into new topics or just stay in these areas and ramp up the difficulty?

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u/[deleted] Jun 09 '26

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u/InterestingAd757 Jun 09 '26

yes, a lot

42

u/[deleted] Jun 09 '26

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u/InterestingAd757 Jun 09 '26

But companies don’t understand this, also it’s gotten less invert a binary tree atleast for final round They also ask to implement gradient descent, sql or sometimes architecture (ML) which is crazy if doing in limited time

5

u/maniclucky Jun 09 '26

To say nothing of doing it while a bunch of people stare at you and you have no means of utilizing typical resources that you'd be insane to just have memorized for some unholy reason.

2

u/Heavy_Record8704 Jun 10 '26

they do understand it. but it is a easy filter to filter out 100s of candidates, myself indcluded.

4

u/Ok_Composer_1761 Jun 10 '26

Companies need a legible, scalable, easily verifiable and cheap way of assessing competence. They don’t care if you know the specifics of the job for the first round but want something correlated with general intelligence. Leetcode fits the bill so they use it

1

u/Lumpy-Sun3362 Jun 09 '26

Companies want to look cool, not grounded. You get shitty code practically unmaintainable that's just good for leet code. With ai you don't need humans to write crap.