Is the term Data Scientist still relevant?

Posting date:14 Mar 2019

You may think this crazy but I posed this very question to a panel of thought-leaders at the Cloud and Cyber Security Expo yesterday and not only did the panel support the idea, the audience were in unanimous agreement.

The panel was formed of Richard Freeman of JustGiving, Alejandro Saucedo of The Institute for Ethical AI and Machine Learning, Mohammad Shokoohi-Yekta of Stanford University, Claus Bendtsen of AstraZeneca and Krish Panesar of Diabetes Digital Media and they presented their case for investing in skills for machine learning success which was fascinating. 

Once the talk was over, the panel opened the room for questions and I couldn’t help but ask what they thought of the current landscape within Data Science. 

Today we have more jobs than suitable candidates and more requirements than skills. We have current ‘scientists’ who were developers, guerrillas or engineers before the trend-cycle who are not remotely equipped to do all of the things now required of them. 

While I don’t think there’s a quick fix for the shrinking talent pool, I am an advocate for devising a list of more specific mandates under an umbrella term of Data Scientist that cater for each branch of ‘Data Science’ as we know it. Be that a Data Engineer, Data Analyst or Researcher, a scientist’s job description is surely a combination of all three and more?

I have recently produced a comprehensive white paper on this very topic which offers insight, opinion and statistics on the evolution of Data Science and includes an on-page debate between thought-leaders on whether it’s time for the term to go.

I would love to hear your views on the matter and see if you think it’s time to scrap the term and if you would like a copy of our white paper – please request a copy below.


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