There are legitimate reasons why stats wins out on interpretability.
1. Scaling is not hard
2. It is obvious to me "how to make these aggregations", but that is because I know statistics. Categories of variables treated as random effects can be interpreted both as a group (via variance parameters of the random effects) and individually via coefficients.
3. Bayesian estimation can even account for correlation of parameters and include it in the posterior prediction.
