Data Scientist: Sexy Is as Sexy Does

Big Data Evangelist, IBM

Everybody has personal passions. It never fails to amaze me how some people can embrace the most tedious line of work, build a rewarding career on it, find deep satisfaction in it, and even evangelize it all tirelessly.

I love data science, advanced analytics and big data, but I recognize that they don’t lend themselves to good cocktail party chit-chat, unless you’re among others who either do it for a living or aspire to. It’s with that in mind that I chuckle every time somebody says data scientist is the “sexiest” occupation of the 21st century. If it were so alluring to the unwashed masses, professional data scientists would be fighting off autograph seekers and paparazzi everywhere they go. Even in analytics-savvy business circles, the data scientist is not necessarily the first person that everybody wants to network with.

Now I realize I should have included “data scientists are sexy beasts” in the myths that I blogged about several months ago. Any sober assessment of this occupation would focus on the fact that it’s highly skilled, requires mastery of arcane technical subject matter, often entails long hours of painstaking development and tuning of statistical models, and, depending on the project, may have an indirect contribution, at best, to the business bottom line. And if you, the data scientist, produce groundbreaking work that transforms your business into an online powerhouse, the credit, in the popular mind, is more likely to go to the CEO who pays your salary, considering that they, not you, took the financial and business risk in greenlighting your project. Or, the credit will go to the larger team of data analytics professionals within which you operate and without whom your project would never have gotten off the ground in the first place.

Entrepreneurship is sexy. So it was highly amusing when a recent LinkedIn discussion group on “wealthiest data scientists” could not name a single person who gained their wealth by continuing to do data science work. Every name that was mentioned is an entrepreneur who built successful software and/or services companies that employ people in various R&D and engineering roles, including (but not limited to) data science. Likewise, any talk of “superstar” data scientists, in an entrepreneurial capacity, is highly speculative, as in my recent blog on the potential for them to shine as central players in the prediction markets of the emerging online economy.

None of what I’m saying is intended to belittle the data scientists of the world. However, we need a serious reality check on the “sexiness” buzz we’ve been hearing in recent months. The inordinate attention paid to author Nate Silver during the late presidential election campaign was just more of that silliness (by the way, he gave a great presentation at this year’s Information On Demand conference. Watch this interview with him.). Fortunately, good ol’ Garry Trudeau did a wonderful send-up of the data-science mania in a recent Doonesbury story-arc, in which a post-election parade featured a “math & science victory lap.”

What’s truly sexy is disruptive business results. Any individual data scientist may only play a partial, indirect role in delivering those results. It’s for that reason that I’ve chosen to alternate my big-data evangelist blogging between two core topics: data scientists, as a key business function, and next best action as a comprehensive framework for translating data science into business results. If you want to know what’s truly sexy about data science, I urge you read any or all of the following application-focused next best action blogs:

If you can deliver revolutionary data science into any of those real-world applications, you’ll grace business magazine covers. You may even be invited by Jon Stewart to exchange witty small talk on basic cable.

Now that’s sexy!