Probability and statistics is applicable everywhere. But the actuarial route is overly specialised for the insurance industry. The ideal data science degree wo

Probability and statistics is applicable everywhere. But the actuarial route is overly specialised for the insurance industry. The ideal data science degree would be computer science and statistics combined. Drop compilers, formal methods, etc. Keep databases, PL, AI/ML, data structures & algos. From stats you get probability, inference, survival analysis, stochastic processes, design of experiments, etc. Throw in some operations research (optimisation) while you’re at it. Comp Sci, Financial Math, Statistics all do the same mathematical track anyway: LA, Calc, Real analysis, Discrete math. I would include a good course covering advanced probability so something based on measure theory. Now you have a general Data Science background to apply in any field.