by Ross McGowan, CivicScience’s VP of Data Science
In case you (or the CivicScience compensation committee) hadn’t heard, data scientists have the sexiest job of the 21st century. You might think it’s a little early to make such a bold proclamation given that we still have a ways to go before the year 2100, but it’s true. Because when we aren’t wading through the tidal wave of recruiting emails we receive each and every day, we get to analyze BIG DATA for a living, which means companies all over the world can’t stop throwing money at us.
Thanks to the amazing bigdatapix tumblr, everyone now has a much stronger sense of what exactly big data is. So we at CivicScience were wondering if we could create a similarly illustrative visual guide that will help people better understand what data science is. After all, there’s no shortage of heated Internet debate as to what data science really means. Is it a rebranding of statistics? Is it a term invented by a nebulous group of people who just want the word scientist to be part of their job title? Or is it an emerging field that will transform all of our lives and prove itself worthy of all the hype?
We’ll let the pictures tell the story…
Below is a helpful image I found that highlights all of the skills one must possess in order to call themselves a data scientist:
Image by Calvin Andrus
Wow! Not only are all of us data scientists experts in highly sophisticated fields like math, statistics, and advanced computing, but we also have things that can’t be taught, like a “hacker mindset.”
Perhaps this is why so many cynics out there say that a true data scientist is harder to find than a . . .
Those people are just jealous of all our LinkedIn profile views.
Whenever I tell someone I’m a data scientist, they usually ask people what my typical day is like. Instead of melting their brains with an onslaught of jargon, I just show them this picture, which comes up over and over if you do a Google image search for “data science”:
An enormous three-dimensional chalkboard is a must for any data scientist’s work station. Also, the concepts we are dealing with are often so complicated that we must resort to using lesser known mathematical notation such as the “rain clouds over oil derricks” sign.
“But wait,” this imaginary person might say, “I thought data scientists use computers. Isn’t that true? I always pictured data scientists as a different version of your stereotypical computer geek.”
Of course we use computers.
And we also look like this . . .
“YES! More insights!!!! Now I can buy an even sexier suit!” After all, being sexy isn’t merely a matter of implementing complicated algorithms – it’s about looking good too.
A big part of our job, as the first image of this post showed you, is statistics. But as we all know, statistics in the year 2015 is almost impossibly lame. Just look at this picture, which is the first result that a Google image search for “statistics” yields:
The machine learning aspect of our job, on the other hand, is much, much cooler. Machine learning practitioners are essentially superior versions of Doctor Manhattan from Watchmen:
In reality, my job as a data scientist at CivicScience is indeed a mosaic of many things – and the power of those magic ingredients recently manifested itself in the form of my top-prize-winning chili at our most recent company-wide chili cook-off:
Please note: We will not be posting about the 2014 buzz phrase “Deep Learning.” Attempting to visualize deep learning is far beyond the grasp of our humble species, and is actually quite dangerous.