Why you should be a Generalist first, Specialist later as a Data Scientist?
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When I first started out in data science, what I wanted to become was dead simple — be a data scientist. Period.
I had no idea if I wanted to become a data science generalist or a specialist. And to be honest, I hadn’t heard of these terms — “generalist” and “specialist” — not until after being in this field for quite some time.
This makes me wonder the pros and cons of each of this and ponder over my career path in data science.
After doing some research online and talking with some people in this field, I’ve made up my thought to become a data science generalist first — aka full stack data scientist if you’d like to call that — and a data science specialist after gaining more experience and skills in different areas.
And you’ll know why in the later section.
In the following writing, we’ll discuss more about generalist and specialist in the context of data science.
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