Hey everyone,
I’m gearing up for a data science interview and could use some advice on how to best prepare. What are some key topics to focus on? Any tips on handling technical questions or behavioral interviews in this field?
Usually, I research the candidates’ backgrounds before an interview to find out how they regard the position or work. This is just a personal preference, but I like to select a few of my most recent projects and create a cover page for each one that provides a succinct overview of the project and a beautifully illustrated example. I then append the code that created it. I take it out and give it to them as I respond to questions they may have regarding something pertaining to a project I’ve already completed.
If you have the leisure, you can read books. Generally speaking, this is how I advise people to get ready for a data science interview:
Practice coding: Before the interview, you can benefit from using leetcode.com to hone your skills in any programming language, regardless of experience level. Particular attention should be paid to features that you may not use daily.
Check out this article about experimenting: The ‘A/B Testing 101’ course on Udemy is a great way to improve your experimental skills. At nearly every organization, I was asked questions about experimentation.
Look for interview questions online: Since so many people interview these days, you can probably find several online. I frequently look on blind.com and glassdoor.com.
Explore interview books: If you have the time, read case question-focused books like “Cracking the PM Interview.”