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Oh crumbs! There I was thinking that by obtaining an estimate of the probabilities of the responses of different groups to an employee survey I was applying a bayesian probalistic approach.

I'm going to have to rethink everything now as since it worked and was quite quick (I didn't even sample using MCMC, just brute force pulled permutations) so it was clearly not a bayesian approach, and I am very very far from one of the top 20 (or 200, or 2000 or 20000, maybe 200000?) researchers...

This may be true for whatever small corner of the data science world you inhabit but it isn’t true in general.

To choose just one example, the analysis of the new UK COVID variant relies on Bayesian modelling, both for the government analysis and the Imperial paper. (https://www.imperial.ac.uk/media/imperial-college/medicine/m...)

Turing.jl[1] is quite usable and isn't slow[2].

[1] - https://turing.ml/dev/ [2] - https://arxiv.org/abs/2002.02702

Can it handle 1000 predictor with 1 million data points?