Why Sckit's fit_transform causes a huge drop in accuracy and all other evaluation metrics?
Without seeing the actual data its kind hard to say.
I do have one speculation, when using the scaler on all data(before the train/test split) you create a data leakage.
Meaning, some of the data the model fitting should not see(the test set) is effectively included in the train set(because the scaler seen it and used if for setting the scales).
This data leakage can cause overfitting and thus lower accuracy score.
Trying doing the scale part on each train/test split(use fit_transform on the train and only transform on the test). 
This is a better practice for model research and obviously closer to how the trained models will perform live(on not seen yet data).