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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.

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Dhairya’s Answer

Hi Jimmy,
Great question. Yes, you can absolutely be a generalist. Often people's careers follow a T shape, where you start with a broad and foundational set of skills and then narrow down a speciality. But it's the not the only way to build a career.

You should look into Data Science consulting and perhaps more broadly management consulting. As a consultant you end up working on many different scoped projects. Having a generalist set of skills here is valuable as each consulting contract can be in a different business verticals (e.g. healthcare, finance, education, etc) and require different set data science methods. Management consulting has evolved into quantitive strategic analysis and may also be appealing to you. Management consulting firms (e.g. Mckinsey, BCG) will hire generalist data scientist to work more technical consulting gigs.
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Carrie’s Answer

Data science is a high demand job. If you have the basics I think it is a good start, however, I do think if you specialized there would be more opportunities for you. If there are fields that you have interest in for example medicine or criminology, you could focus on learning some of these. If you focus on specific programs that those organizations use to read and interpret their data in those fields this is a leg up. I think there is more opportunity for moving up if you specialize.
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Holly’s Answer

Hi Jimmy - I agree with Carrie. Data scientists are in high demand. Almost every industry today can derive value from these skillsets. I would recommend spending time thinking about what problems excite you and that you would like to solve. Then look into data science opportunities in those areas. I have not done any analysis on this topic, but there may be some industries where there is more demand than others, so that could also be a factor you evaluate. Good luck!
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Rahul’s Answer

Is there a place for generalists with domain knowledge that relates to the task at hand? Yes, absolutely yes!
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 :)
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Gillian’s Answer

Hi Jimmy!

Just going to mimic everyone’s opening answer and say that, you will have absolutely no problem finding a vast quantity of job listings for generic data science jobs; they’re usually listed as “Data Scientist”. Usually those looking for specialists will include the type of specialization in the job title or description.

When I first started in data science I felt overwhelmed with the amount it specializations to choose from and was in a very similar predicament to you. Through my two generic data science jobs that I have had so far, I am starting to discover what niches of data science I prefer and which I don’t. This is a process that takes time to allow you to explore and get good at these subcategories, so definitely explore generic data science at a jumping off point.

If you’re going to go back to school for this, I highly recommend working an internship in it at the same time, as it will greatly increase your odds of being hired directly after (and sometimes slightly before) graduation.

Gillian recommends the following next steps:

Research and practice generic data science principles in your free time to make sure that this is something that you are truly passionate about.
Research ‘data scientist’ job offerings either through linkedIn or Indeed and see how many of the skills you qualify for and which you need to brush up on.
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