A Data Science Central Community
Summary: Not everyone wants to invest the time and money to become a data scientist, and if you’re mid-career the barriers are even higher. If you still want to be deeply involved in the new data-driven economy and well paid, the growth rate and opportunities as a data engineer or business analyst need to be on your radar screen.
OK, given that Data Scientist is still the sexiest job in America, what happens if you can’t or don’t want to invest your time and money to achieve that credential?
Seldom a week goes by without someone posing a question about how to switch from their existing career into data science. While I personally believe that you can’t have more fun anywhere else, there are many legitimate barriers facing those wanting to switch. Especially if you are more than 5 or 10 years out of school.
We wrote at length about this in “Some Thoughts on Mid-Career Switching Into Data Science”. It’s one of our most widely read articles so apparently there are a lot of folks trying to figure this out. Basically we said there are no shortcuts. While it will be intellectually and eventually financially rewarding, it’s hard if your career is already underway.
Even if you are mid-education, the full blown data science credential isn’t right for everyone. And with the new corporate orientation toward democratizing data (code word for self-service), anyone who wants to get down into the data will have plenty of opportunity to do so.
The good news in an increasingly data-driven world is that there is a pyramid of supporting roles growing even faster than the data scientist role. They’re in demand. They pay well, and you may indeed find it easier to leverage your current skills into one of these roles, perhaps with the aid of a MOOC, a boot camp, or even OJT.
We’re talking about two roles that have existed for some time, Data Engineer and Business Analyst.
Read the full article, by Bill Vorhies, here.