Is there a place for data science generalists in the job market?
With some introspection these last few months, I found that no one field (e.g, analytics, natural language processing, experimentation, etc) in the data science space really draws me (though all are very interesting in their own way). With that being said, is it frowned upon in the job market to be more of a generalist data scientist than a specialist data scientist?
In the past, my academic journey has allowed me to earn degrees in history, anthropology, mathematics, computer science, statistics, economics, political science. I suppose this conundrum I'm having in the data science space closely mirrors my experience back when I was an undergraduate.
Perhaps a company or business may derive more value from someone who is more specialized in their subfield than someone who is fluent in most modalities but not particularly an expert in any one subfield.
Though I would have to also add that domain knowledge and understanding of business context are important skills to have regardless if you're a generalist or specialist data scientist based on my what I've observed.
You can definitely come in as a generalist and then specialize in one or more techniques, depending on the scope and need for applying those in your place of work - a lot of professionals I've come across, were able to pick up skills and the required know how while working on projects.
So, the sky's your limit :)