Are there subsections of LeetCode data scientists should focus for DS interview?

I have a data scientist/machine learning engineer interview coming up from a company that focuses on financial risk analytics using stats and ML/AI/simulations. I was told the next round of interview involves leetcode type questions (i.e., data structure and algorithm), along with ML concept questions.

I haven't really practiced leetcode before, and some of the specific categories seem pretty hard to grasp or apply as a DS (For example, do I need to be good at DFS/BFS, backtracking, memoization, etc?). …

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