Dummies Variables and Scaling in Regression Problems
Would this approach create an inappropriate bias considering the different scale from dummies and the scaler numerical? Or, at least, is it correct?

&quot;It is fine&quot; because One-Hot-Encoded features don't have a very large scale. Issue of scale comes when features are at a very different scale e.g. 1 vs 105 etc.
Standardizing them will disturb the sparsity(i.e. log of zeroes). Normalizing them will not have any impact.
What is incorrect here is -
 You are standardizing the dataset prior to the split. You must do the other way round.
What is optional here is -
 You don't need scaling and OHE for a Tree-based model. Just label encode, split and move.