Summary:  If you are mid-career and thinking about switching into data science here are some things to think about in planning your journey.

 

We get lots of inquiries from readers asking for career advice and many of these identify as mid-career looking to switch into data science.  If you’re in this group you face some of the same challenges beginners do but also some that are unique to your circumstance.  Here are some thoughts and observations that may be valuable.

 

About You

When folks self-identify as mid-career they usually cite 10 or 20 years experience.  By my way of thinking that makes you most likely 30 or 40 years old.  The majority of these folks say they are involved with IT, perhaps as programmer, analyst, admin, or similar.  Some are in an area of operations that is heavily data driven.  Most have a bachelor’s degree but some do not.  It’s you I’m thinking about in the following notes.

As you read this you may well say ‘this doesn’t apply to me, I’m different’.  I am writing for the middle of the standard distribution.  If you know you’re a two or three-sigma guy or gal, my hat’s off to you.

Why Switch At All?

Because data science is hot!  I mean we are constantly exposed to articles that call this the best job in America and from an insiders perspective I think they’re right.  The work is interesting and challenging.  We work with tools that are very rapidly evolving for the better.  This means we have to be life-long learners and that’s a good thing.

Everyone is aware that there is a structural shortage of qualified data scientists.  Companies are actively hiring and can’t find enough of us which is reflected in the well above average compensation.

Presumably there is also a level of dissatisfaction with the rewards from the 10 or 20 years you’ve put in.  If you’re looking for greener pastures this is a good place to look.