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Return of the Data Scientist

by Svetlana Sicular  |  March 27, 2015  |  2 Comments

I am convinced, data science was not born in 2008 — it’s just the term “data scientist” which has been coined that year.  I wrote a blog post Data Scientist – Mystified in 2012. At the time, data science was mystified, glorified and made mathematics sexy. I liked what it did to math, but I was mystified too: Mysterious creatures who called themselves “data scientists” did not fit my mental profile of this occupation. I did not have to use my imagination to picture people who can perform data science — I knew them, but they were not among the mysterious creatures.

Debates over the definition of a data scientist perplexed me: Business analyst in California. Statistician under the age of 35. For sure, not a college dropout. But what about those bright thinkers who were performing data magic before 2008? What happened to the diverse teams of quantum physicists, PhDs in chemistry and numerous statisticians whom I have seen in fraud detection and denial of service attacks deflection before the invention of the term “data scientist”?

And then things started happening. A client timidly asked a weird question, “Can we rename our team from Analytics to Data Sciences?” I didn’t think that I was the best person to give a permission, but why not – be my guest. A year later, this client met me at a conference and said thank you. It turned out, after becoming Data Sciences, this team got much more attention and respect in the organization, as well as more budget, and greater raises too. Data sciences turned to a self-fulfilling prophecy. My contribution to this metamorphose was negligible, but I said, “You are welcome” and “Well deserved.”

Today, let me challenge you: Picture a number one data scientist on Kaggle. While you are unleashing all your enormous imagination to draw his portrait, I’ll entertain you by the fact that Kaggle calls itself “the world’s largest community of data scientists who compete with each other.” Now, whom did you paint? Or did you cheat and went to their leaderboard? Then you discovered Owen from NYC, he introduced himself as:

Trying to find the right question to ask.

That’s a hint to the glorified business analysts in California who say in a mystifying voice, “Data will tell you.” Yes, it will — if you know what to ask.

Did you notice on the Kaggle leaderboard Jose A. Guerrero from Spain? He was a celebrity guest at the last (and first) H2O World. Does he fit your mental portrait of a data scientist? He has more than 25 years of experience in health sector. While statisticians were outgrowing 35, Jose A Guerrero won over 40 data science challenges. Also, an epitome of a data scientist to me has always been Bob Grossman. That’s how he describes himself:

I’m a data scientist who has been working with big data since 1988.

That’s exactly my point! People who have been working with data that is now big finally started calling themselves “data scientists.” They returned! Here they are!

Look forward to see more data scientists — who returned! — at the Gartner BI and Analytics Summit. Follow hashtag #GartnerBI next week.


Follow Svetlana on Twitter @Sve_Sic

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Category: data-scientist  analytics  data  

Tags: data-scientist  data-paprazzi  information-everywhere  

Svetlana Sicular
Research VP
6 years at Gartner
23 years IT industry

Svetlana Sicular is passionate about bringing analytics to domain experts and helping organizations successfully compete by applying their business acumen in analytics and data science. She is convinced that domain expertise and high-value data are the greatest assets that companies should monetize in new analytics applications. Read Full Bio

Thoughts on Return of the Data Scientist

  1. Punit Lohani says:

    that’s an interesting article. in fact, if Tom Davenport in his article Analytics 3.0 takes us through the history of analytics. It really depends on what’s your definition of data science. I too believe that we have been using data science for long.

  2. […] Gartner analyst Svetlana Sicular highlights[1], “That’s a hint to the glorified business analysts in California who say in a […]

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