* Moving data around - mostly using Excel + SQL, though R is growing in popularity
* Using that data to calculate figures that are significant to the business - including premiums, IRRs, profit margins, and the value of future claims
* Presenting the results of those calculations to management and recommending a course of action
I'm not sure what "old-school original data scientists" do/did or how similar this is.
But actuaries' main value-adds are (1) building and pricing new products and product features and (2) helping management understand the financial results and their business implications. If you're just re-pricing a commodity product like term life or home/auto insurance, a lot of the pricing can be (and is) automated. But that's where companies have started building out more complex ML-based pricing, and actuaries are heavily involved in building and steering that functionality and explaining the results.
If you can come up with a compelling way to automate a significant portion of that work while still providing results that insurers' CFOs and Chief Actuaries will sign off on, sign me up. But in general, if you're looking for automation opportunities in insurance, there's far more low-hanging fruit on the operations side than in actuarial. Same goes for finance and accounting, though to a lesser extent than operations.
My mother is an actuary. She was a stay at home mom for 25 years but returned to the workforce about 5 years ago and recently became VP at a large insurance company.
She says she’s always enjoyed her work as an actuary, and she preferred it over college math instruction, which she could do because FSAs are considered PhD-level. (And did while her 6 children were home.)