Preparing for data scientist/data analyst interviews is a time-consuming activity, but the prepping time can be significantly decreased if you have prior experience in the field and/or have a list of the right resources for each topic that potentially will show up in the interviews so that you can focus your efforts. Even though data scientists and data analysts are different career paths in the data world (if you don’t know the differences yet, check out my post on the subject), there are a lot of overlaps when it comes to topics covered in interviews.
In my previous post, the first part of my interview prep guide, I outlined the commonly tested areas that appear in most data-related job interviews (those questions are commonly asked in interviews for data scientists, data analysts, data engineers as well as technical product managers). In this post, I’m going to zoom in and focus specifically on the interviews for data scientists and data analysts; I have been interviewed by dozens of companies in the Valley for those roles and have compiled a list of useful resources along the way. If you are interviewing for a data scientist/data analyst position, make sure you brush up on these topics in addition to the ones I outlined in my previous post.

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