Other than Kaggle
LeetCode for Python questions, easy gets you past coding rounds at most companies, DataLemur for SQL interview prep, Cracking the PM Interview is good for product data science questions and more open-ended business-y DS case problems. For ML interview questions, just knowing the most important concepts + terminology from Intro to Statistical Learning is good (most interviews ask about classical techniques, so don't worry if you aren't a deep learning pro). Practical Stats is good for Prob/Stat conceptual questions (but doesn't exactly map to what interviews test... unfortunately at FAANG + Wall Street you will find the occasional probability brain teaser).
You can also check out the book "Ace the Data Science Interview" on Amazon, which is like "Cracking the Coding Interview" but for Data Science & ML interviews. It covers all the topics mentioned above, but I'm a tad biased since I wrote the book!
Leetcode. Unfortunately.
Hey there. Data scientist here preparing for a first round of interviews at Google for a researcher position.
I was wondering if anyone here have been interviewed for this position before. The contents are
1st: Statistics + communication. 2nd: Data analysis + communication.
I am reviewing topics such as expectation, variance, probability, bayes theorem, hypothesis testing, confidence interval and A/B tests.
Any tips, leaked questions, material for study? I appreciate a lot.
Videos
Haven't heard after almost a week past screening round? What are the expected timeline!
What goes into preparing for Google Data Scientist Internship? I have two 45 minute technical interviews but I am not sure if it will only be a coding round. Any tips, advice, resources would be greatly appreciated!