Everyone knows the job market in tech is hard straight away. On this post, I’m breaking down a comprehensive guide on the best way to prepare for Data Science and ML interviews in order that you might have the most effective possible probability of success when interviewing in a competitive field.
The important thing thing that I do in a different way with interview prep is, essentially, over-prepare. I put in a ton of labor prematurely to anticipate what could be covered, and dig deep into studying those topics in order that it looks like I got here up with clever, well thought-out solutions on the fly.
After you submit an application, step one is usually a brief call with the recruiter. This call will likely be straightforward, but you continue to can — and will — prepare to set yourself apart.
Here’s what you want to do:
First, write and practice your elevator pitch. This ought to be short — max three to 5 sentences. There’s a format for this that I actually like: One sentence for where you’re, one for where you come from, and one for where you should go.
This ought to be super high-level, and is barely to present the recruiter a general idea of the type of work you do, and drop a few keywords to point out that you might have relevant…
