Out of curiosity, what are some other, powerful, statistical branches besides those used in "data sciences" ? (honest question, I just completed a MSc in data sciences but I must admit I don't know much besides that)
I’d recommend generalized linear models which are a subset of linear mixed models. These are the driving force for financial services.
The model building process for these translates well to other types of models.
Decision trees and random forests show up too.
I think data science is great in that it exposes one to programming and technology moreso than a focus in math or stats, I was mostly complaining about the marketing I’ve seen surrounding AI. I recall listening to a few mba consultants claiming that they could improve a business process significantly by using ML even though there was sparse inaccurate data available and they had no modeling background.
Overall I think AI models are interesting and often useful (although not sure what fits under the umbrella), but am tired of the hype, strong opinions, and amount of claimed expertise.
