[iamdave]

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.

[tomrod]

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.