Companies are desperately seeking mysterious creatures — data scientists. Some people claim to have seen them in LinkedIn and Target. Perhaps, those were encounters with data scientists from LinkedIn that shop at Target? Or Target data scientists who search on LinkedIn for pregnant teens? Either way, the companies are desperate (except for LinkedIn and Target). But they are seeking anyway. Why? Because nowadays, everyone wants to compete in the new, data-driven economy, where Google and Amazon have already figured out “data alchemy” — turning data into gold.
A data scientist symbolizes to organizations a gaping hole: a magic that can turn big data into big gold by making sense of vast amounts and multiplicity of senseless bits and bytes (or zettabits and petabytes?). The data scientist is a savior who (if found) can solve all big data problems, so companies will not have to worry about figuring out how to do it themselves, all they need is to catch two or three really good data scientists, no matter what they are.
I heard a couple of definitions: a data scientist is 1) a data analyst in California or 2) a statistician under 35. Either make 10% above the salary of common data analysts and statisticians, so the latter learn how to position themselves as data scientists. Google shows that web search interest for “data scientist”picked up back in 2010, but the #1 Google search phrase on the subject is “data scientist salary”, which reflects both supply and demand. The second top search is “data scientist jobs”. I confess, I did it too: I copied around two dozens job postings with removed titles and other HR nomenclatures and made a word cloud.
The picture, as well as my more in-depth research, show that companies should look within. Organizations already have people who know their own data better than mystical data scientists — this is a key. The internal people already gained experience and ability to model, research and analyze. Learning Hadoop is easier than learning the company’s business. What is left? To form a strong team of technology and business experts and supportive management who creates a safe environment for innovation. The team members with diverse skills will inspire and enrich each other: their combined knowledge will be the power to develop analysis and bring new insights.
After the team achieves results, compare the size of data with the size of science on the picture. By the way, did you notice that large is greater than big but both are relatively insignificant?
Read Complimentary Relevant Research
Organizing for Big Data Through Better Process and Governance
With big data past the Peak of Inflated Expectations on the Hype Cycle, organizations are addressing next-level challenges and asking,...
View Relevant Webinars
How to Sell a Big Data Initiative to Senior Management
Engineers, architects and analytics leaders are excited about new technologies and grasp them quickly. But techies' biggest challenge...
Category: data-scientist big-data cloud data-paprazzi innovation inquire-within skills
Tags: data-scientist analysis analytics big-data california catalyst data data-janitor data-paprazzi data-spy experience hadoop hiring hr innovation jobs salary scientists search teams
Comments or opinions expressed on this blog are those of the individual contributors only, and do not necessarily represent the views of Gartner, Inc. or its management. Readers may copy and redistribute blog postings on other blogs, or otherwise for private, non-commercial or journalistic purposes, with attribution to Gartner. This content may not be used for any other purposes in any other formats or media. The content on this blog is provided on an "as-is" basis. Gartner shall not be liable for any damages whatsoever arising out of the content or use of this blog.