Everyone wants a Data Scientist. It's cool, it's sexy, it's the job of the century but what do they actually do?
Every day I speak with clients eager to grow out their Data Science function hopeful that in hiring a “Data Scientist” their business will become enlightened and pass into commercial nirvana. It’s not always so easy.
All too often once the company have been successful in hiring the Ivy League “Unicorn” with cutting edge Machine Learning Algorithm development skills they hand them a bunch of dirty data and say: “Can you clean that please?”
When the Angel Round funding lands the Data Scientist is the “go-to” trophy hire, an injection of sexiness that will bring about the “Uberisation” of your disruptive Bricklaying App.
Sometimes it pays to have a horse before you buy a cart. Or is that a cart before the horse? It’s a chicken and egg situation. Perhaps buy lots of Chickens and Horses and somehow the cart will learn to pull itself. That’s Machine Learning in an eggshell.
Businesses and technology leaders have learned a lot about the importance of data and the need for data scientists, but do they understand what the role of a data scientist should entail?