What does it take to become a data scientist?

In Blog by Gregg Weldon

The basis of analyzing data is constantly asking why things are the way they are. One of the lessons I stress when training new data analysts is to always ask the question, “Why?”. “Why does my data look this way?” “Why do people behave this way?” Why is my dependent variable split this way?” “Why are my results showing these trends?” These and many other “why” questions are what leads to building the best, most predictive models.

Among the most important soft skills in a successful data analyst is having a natural curiosity about the world around us, a healthy dose of common sense, and a talent at logic and deductive reasoning.

These skills give analysts both the desire and the ability to dig deep into the data and unearth nuggets of information that others may miss; nuggets that can identify future behavior in consumers. In that way, people who liked taking things apart as children to see how they operate are naturals for this industry. We want people who try to see patterns in everyday occurrences, and find a way to make some sense from them.

A good data analyst gazes into chaos and tries to sort it out into some type of reasonable order. Not because we have to, but because we find it enjoyable!

To put it simply, becoming a “data scientist” doesn’t require a lab coat, or mountains of spreadsheets (okay, maybe rolling hills); it all starts with curiosity. If you’re interested in learning more about our scientific approach to data, this quick video is the perfect primer for anyone interested in learning more about the field.