Is Data Scientist the Sexiest Job of Our Time?

Harvard Business Review proclaims data scientist the "sexiest job of the 21st century"

2 min read
Is Data Scientist the Sexiest Job of Our Time?

Like many start-up companies, business networking site LinkedIn once struggled to capitalize on the mountains of data generated by its users. Then, in 2006, a new hire, data scientist Jonathan Goldman, swept in and tamed the unwieldy data mess in a way that launched the company to the next level. Goldman extracted patterns from the connections between LinkedIn's users, and came up with a way to suggest to those users other people they may know. The "people you may know" feature created millions of new page views, and LinkedIn's growth went skyward. 

Sexy? The folks at Harvard Business Review think so, and in their October issue they proclaimed the data scientist the sexiest job of the 21st century. The authors of the article, Thomas H. Davenport, a visiting professor at Harvard Business School, and D.J. Patil, a data scientist at Greylock Partners, liken the profession to the Wall Street quants of the 1980s, and the computer engineers of the 1990s. "If 'sexy' means having rare qualities that are much in demand, data scientists are already there," they wrote.

A data scientist's job description goes like this: Make discoveries while swimming in data. Possess an intense curiosity. Bring structure to formless data and make analysis possible, all while having a feel for business issues and an empathy for customers. Advise executives on how to use the information to make better products.

What kind of professional can do all of these things? The rare kind with the powerful combination of skills that let them wear the hats of data hacker, analyst, communicator, and trusted adviser—all of which must be applied to a specific technology or product. (Spectrum last year identified 26 variations of data mining in IT).

Because more and more companies need someone with these skills, the demand for data scientists is exceeding the supply. These professionals garner high salaries and large stock option packages, the authors found in an informal survey. But more than that, data scientists want to be "on the bridge"-—a reference to Star Trek, in which Captain James Kirk relies on data supplied by Mr. Spock. They want to be involved in decision making, not just advising. 

The dearth of data scientists of this caliber has become a constraint on some sectors, forcing people to devise their own ways of generating and locating talent. Greylock Partners, a venture firm, has built its own specialized recruiting team to channel talent to the businesses in its portfolio. And after acquiring the big data firm Greenplum, EMC launched a data science and big data analytics training and certification program. 

Once companies snag a good data scientist, it's hard to hold onto him or her. LinkedIn lost Jonathan Goldman to Aster Data, which lost him to Level Up Analytics, a company Goldman co-founded.

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You’d expectthe longest and most costly phase in the lifecycle of a software product to be the initial development of the system, when all those great features are first imagined and then created. In fact, the hardest part comes later, during the maintenance phase. That’s when programmers pay the price for the shortcuts they took during development.

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