ANECDOTE TIME! And actually a career related question:

I'm an absolute nerd for sports stats, and have a friend that moved out of the finance/BI world in the hospitality sector and landed herself an impressive gig at ESPN-of all things, as a stats editor.

It seems a relevant jaunt (because all I know of her profession is that she's an incredible mathematician) but the gap seems wide just from a perspective of domain knowledge; she openly states not caring at all for sports but the new job location puts her close to family.

My question is: is Data Science so applied that one can make that kind of jump domains easily? This gal is one of the smartest people I know but the more I look into what it is you folks do, the more I am simultaneously intimidated yet interested in the field.

Domain knowledge is always useful. But can also introduce biases in one's analysis.

For these types of professional roles you generally see specialized teams in three broad groups: data engineers, modelers/analysts, domain experts. Unicorns sometimes exist, but usually you see T-type experience with depth in one of the three.