[jstx1]

First you need to figure out if you're applying for a product data science position, or for an ML position, or for an ML position with a data science title.

1. Interview query and strata scratch focus more on interviews for "product data scientists" - those interviews focus a lot of SQL, product metrics, A/B testing etc. You can also do SQL problems on leetcode for those types of positions.

2. Deep learning interviews book for ML positions - https://github.com/BoltzmannEntropy/interviews.ai - it's a bit too deep and advanced for most interviews though so don't be intimidated if you can't cover everything. Don't read this book if you're applying for a product DS position (and vice versa). You can also replace this with an ML theory book of your choice if you like.

3. For ML positions you still need leetcode and CTCI because those questions come up for ML positions anyway.

4. Take-homes. Expect more take-homes than the average for SWE positions.

[morelandjs]

Just to add that not all ML positions are Deep Learning. Still good info to know though.