“Data Scientist” is the sexiest job of the 21st century. The Harvard Business Review made this claim last October and it seems that everyone (including your grandmother) has been repeating it ever since.
But what exactly does a data scientist do and what specifically makes her/him sexy (aside from the clout and the big paycheck)? And perhaps, as importantly, what do you have to know — and where do you get the “stuff” that you need — to land the hottest gig of the 21st century?
To answer these questions, we’re providing you with an Infographic below (courtesy of FICO) and insights from some of the hottest companies in Big Data.
Data Scientist: Skills in Demand, Not Degrees
First off, there is no question that Data Scientists and Big Data Wranglers are in high demand. FICO recently reported that there was a 15,000% increase in job postings for data scientists between summer 2011 and summer 2012. Add to that that 1.5 million more data-literate managers will be needed by 2018, and you’ve got a lot of jobs.
But you won’t find many, if any, data scientists in the working world with “data scientist” on their diploma. In fact, some of the world’s most talked about data scientists didn’t know that they wanted to be data scientists when they began their careers, so getting that specific degree (and it’s doubtful that any formal data science programs existed at universities five years ago) probably isn’t key to being successful.
We did a quick perusal through the profiles of some of today’s leading data scientists to see what they were studying before they earned their fancy titles, here’s what we found: Jeff Hammerbacher and DJ Patil studied Mathematics; Hilary Mason studied Computer Science; Doug Cutting, co-founder of Hadoop, has an AB in linguistics and Jonathan Goldman one of LinkedIn’s earliest data scientists studied Physics.
And we’re pretty sure that few, if any, of these folks applied for a role as a “data scientist” when they got their first jobs, so if you’re not a data scientist right now, but you think that you’ve got what it takes to become one, there’s room for hope, and plenty of it.
Consider that some of the companies that employ the world’s most prominent data scientists aren’t even sure of exactly what a data scientist’s academic background should look like.
"The particular set of skills required to perform data science in practice is both still being defined and hard to accumulate through conventional curricula,” says Ryan Goldman, Services and Training, marketing manager, Cloudera. He adds that the data scientist role is relatively new and mainly populated by “people who are better at statistics than any software engineer and better at software engineering than any statistician,” a phrase he’s borrowed from Josh Wills, Cloudera’s Director of Data Science.
Lisa Arthur, Chief Marketing Officer at Teradata adds that a softer set of skills is required as well
Companies are in need of employees who can sort through enormous data sets to find valuable insights, but few people have the right mix of technical and business know-how,” she says. “While an IT degree is helpful, it ultimately comes down to a potential employee’s softer skills. Can they identify insights that their more technical colleagues may not see? Can they present data-driven findings in a way that the board room understands? These are the types of questions companies are asking, and a degree cannot necessarily equip graduates with these skills.”
And though degree programs are emerging, it’s yet to be seen as to whose programs will be best and what their worth will be.
“For now given the scarcity of talent, learning about big data technologies thoroughly and being able to apply them consistently may be enough to land a job,” says Jonathan Ellis, Co-founder and CTO of DataStax.
Training is the Ticket to Fill the Data Scientist Gap
Degree programs may be great (once they’re here), but for those with the right backgrounds, training may be the ticket.
Even if plenty of Data Scientist degree programs were available at most universities (Note: we’re not taking anything away from those who have them), they wouldn’t provide the large number of data scientists that Enterprises need now. As a result, some Big Data vendors are offering training programs, some of which require deep technical and analytical abilities as prerequisites, others may be suitable for Java junkies and relational database DBA’s.
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