Last week I wrote a blog post on how to pass the dreaded data science take home challenge. You can read the full blog post on Medium, but I wanted to summarize my tips into something succinct for anyone that's looking for help on their data science take home challenges. 

Hi everyone, a few weeks ago I ended up doing a podcast collaborated with Towards Data Science, a medium publication that aggregates posts on everything related to data science and machine learning. 

You can listen to full podcast here. We mainly talked about my career starting from entering data science as a new grad without any experience to working at a few different startups. I wanted to outline a few points that were made during the podcast. 

A friend of mine called me the other day out of the blue in a state of frustration.

Let’s call him Don.

Don was ranting about his latest data science interview he had thirty minutes ago. His interviewer had asked him an interview question over the phone that was given two example tables, could he write a query that would involve joining both tables to return a value. 

Here at Interview Query, we focus a lot on questions and take-homes that are asked of you during the data science interview process at top technology companies, but today we’re going to focus on questions you should ask.

Remember when the term data scientist first came out in early 2010? Harvard Business Review coined it as the The Sexiest Job of the 21st Century and prompted everyone who ever worked in statistics or analytics to immediately back-change their positions and titles for recruiters on Linkedin madly searching for these so-called unicorn data scientists.

I’ve interviewed a lot of data scientist candidates and have found there are a a lot of SQL interview questions for data science that eventually boil down to three generalized types of conceptual understandings.