The Sexiest Job of the 21st Century
The sexiest job of the 21st century is not a social media entrepreneur nor Hollywood producer. If you take a cue from the Harvard Business Review, the title goes to data scientists. That’s right. Data scientist, as in, the type of person who can write computer code and harness the power of big data to come up with innovative ways to use it for companies like Google (GOOG), Amazon (AMZN), and Yahoo! (YHOO). (Full disclosure in case you didn’t notice – this writer works for Yahoo!)
Related: ‘Big Data’ Generates Big Returns: Q&A With VC Roger Ehrenberg
Of course you have to buy the logic that what makes a career “sexy” is when demand for your skills outstrips supply, allowing you to command a sizable paycheck and options (as in the kind where there are plenty of employers that would welcome your talent).
Just how in demand are these candidates?
PEHub cites a tech recruiter who says he’s aware of thousands of data science jobs awaiting candidates in the Silicon Valley area. Nationally, McKinsey & Co. estimates the U.S. has as many as 190,000 fewer people with analytic expertise than needed.
This affords big data bigwigs the luxury of choice and a hefty payoff.
PEHub reports pay for data scientists is upwards of $225,000 even for people straight out of graduate school, up from $125,000 just a few years ago. For someone with a few years of experience working in the field, pay can reach much higher. One Seattle software-company CEO describes candidates with these skillsets “almost like unicorns.” One got away from the executive when Microsoft approached the data scientist with a $650,000 salary plus bonuses.
Related: How a 17-Year-Old Brit Is Revolutionizing Mobile News
Courtney Reagan, CNBC reporter and host of Big Data Download, a twice daily show you can find right here on Yahoo! Finance, discusses these unique data-mining skills and what businesses are clamoring for them in the accompanying video.
“They’re not really looking for people who have these computer science backgrounds or folks that perhaps would have previously gone to a hedge fund or a quant team to work on the algorithms, but people from all sorts of other majors – maybe science majors, ecology majors, people who have a different way of thinking about data,” Reagan explains. “There is no major or school you go to learn to be a data scientists.”
The Harvard Business Review actually compares these “data scientists” to the quants of 1980s and 1990s on Wall Street, who pioneered “financial engineering” and algorithmic trading.
Related: Why Warren Buffett is Wrong about High-Frequency Trading