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In 2010 I was training ANNs using libFANN and my own implementation of “early stopping”, then building ensembles of them. I was also using various clustering and regression algorithms to predict the expected results of CFD and FEA simulations of turbocharger components.
Was I a Data Scientist?
No. Data Science was/is just one skill in the rather large skill set I acquired through practice and learning, in to get my job done effectively as a Development Engineer.
Domain knowledge makes all the difference. If you don’t understand the domain, you are not a data scientist or machine learning engineer; you are a mere computer operator; an I/O component, a slow human in the loop.
It’s the same reason that, for example, we don’t typically let people who don’t understand turbomachinery design go bananas on building finite element simulation models of turbines; if we did, they would be the equivalent of monkeys with typewriters.
Domain knowledge is key.
Data Science is a skillset.
Call the role whatever, but the person in the role must know the domain of application and the know-how of data science, experimental data analysis, visualization, etc.
