Never get stumped again
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We all know the job market in tech is tough right now. In this post, I’m breaking down a comprehensive guide on how to prepare for Data Science and ML interviews so that you have the best possible chance of success when interviewing in a competitive field.
The key thing that I do differently with interview prep is, essentially, over-prepare. I put in a ton of work in advance to anticipate what might be covered, and dig deep into studying those topics so that it looks like I came up with clever, well thought-out solutions on the fly.
After you submit an application, the first step is typically a short call with the recruiter. This call is usually straightforward, but you still can — and should — prepare to set yourself apart.
Here’s what you need to do:
First, write and practice your elevator pitch. This should be short — max three to five sentences. There’s a format for this that I really like: One sentence for where you are, one for where you come from, and one for where you want to go.
This should be super high-level, and is only to give the recruiter a general idea of the kind of work you do, and drop a couple of keywords to show that you have relevant…