Data Science was coined in 2001 by William Cleveland who wrote ‘Data Science: An Action Plan for Expanding the Technical Areas of the Field of Statistics’ but while history paints it at almost a decade old, the phrase was popularised several years later by D.J. Patil and Jeff Hammerbacher who described themselves as Data Scientists at LinkedIn and Facebook.
Over the past decade, the role has been elevated in what has been widely described as the third industrial revolution. It has been coined the sexiest job of the 21st century and every organisation wants one in the move to Big Data but has the role evolved past its meaning and is it time we replaced it?
Patil famously described his role as ‘making big data small’ but as the role has come to incorporate so much more; with expectations rocketing and a talent pool shrinking, I explore whether it’s time to scrap the term Data Scientist altogether and replace it with a list of more specific mandates.
I meet thought-leaders from across the world and ask them this very question and to my; and perhaps your, surprise, the movement is gaining momentum with experts claiming the term Data Scientist has become muddied, misunderstood, devalued and essentially, redundant.
In this insight paper we will look back at Data Science before it became fashionable, discuss its vast achievements and see what the future holds. We will also inspect the people challenges facing the data space and follow its evolution to try and find a solution for the forever-shrinking pool of technological talent.
"It's been a pleasure working with Joanne and I would highly recommend Stanton House to others (and have done so!). Personal service and a demonstrated passion to support client and candidates throughout the process to ensure the best outcomes is, for me, a differentiating factor."