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As a data scientist I can testify that it's really two jobs -- 80% or more data engineering and 20% or less analysis. When the enterprise is small it's reasonab
by Jeff_Brown 3y ago
As a data scientist I can testify that it's really two jobs -- 80% or more data engineering and 20% or less analysis. When the enterprise is small it's reasonable to want people who do both. Once it's big enough, though, specialization makes more sense -- you don't need all your data engineers to know how to draw conclusions from the data.
Moreover the people analyzing it don't need to be data scientists -- they can as easily be statisticians, economists, geneticists, etc.
- tomrod 3y ago> Moreover the people analyzing it don't need to be data scientists -- they can as easily be statisticians, economists, geneticists, etc. While data science is a newer academic field, most of its practitioners come from statistics, economics, genetics, etc.! (I say this as a 10-year data scientist who is an economist).
- stanleydrew 3y ago> you don't need all your data engineers to know how to draw conclusions from the data. I'm not sure this is accurate. To the extent that a data project is underspecified (which, let's be honest, all projects are) then the engineers will end up making some decision somewhere that may have an impact on what's available for analysis. If the engineers have some understanding of project motivation and hypotheses then they'll make better decisions.
- nerdponx 3y agoI think you're both saying the same thing. Data engineers don't need to be able to also do all of the data science, but they should know enough to make good decisions about data projects.