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In 2018, Fast Company declared ‘Data Scientist’ as the best job in America for the third year in a row!
How many of you have noticed people suddenly calling themselves data scientists?
So many people out there are suddenly calling themselves ‘data scientists’ because it’s been called things such as the sexiest job of the 21st century. That’s just the problem – you have far too many people who are falling into data science without having enough background to really answer the questions that no one else can answer, and are becoming disillusioned with the field.
Matt goes on to state:
With the increasing power of user-friendly tools and GUIs, and a data science course seemingly available on every website, being able to perform data science will eventually be like being competent in Excel. Just knowing the ins and outs of data science as a skill will not be enough. The tools will be powerful enough to handle the data “sciencey” aspects, and the fundamental concepts will be taught throughout school, evolving data science into a skill integral to every job role, not a title. There will be no more data scientist roles, just roles that use data science.
While I agree there will be many roles that use data science through the use of intuitive applications and tools which are derived from data science components and machine learning – it will not cause the death of data science.
I go into what I believe is a data scientist here, but if you want to skip that, my TL;DR is that data science is essentially a blend of having business domain knowledge, coupled with math (statistics and probability), computer science (data analysis, programming), and the ability the communicate all of this through data visualization (dashboards, quantitative/qualitative reporting) and storytelling.
As the data science profession settles within the scope of businesses better, there will be plenty of opportunities available.
I believe that true data science isn’t just a science, but also an art. The art of data science is how we apply our domain knowledge and strategic thinking in answering questions and solving of problems. As I see it, the role of the data scientist is to really understand what the problem is that you are trying to solve, and then figure out a way to solve it.
Data scientists without domain knowledge are how we add risks to the data science profession by producing suboptimal results due to their Rumsfeldian “unknown unknowns”.
This post is also available at the original source ziyadnazem.com