Hyperparameter tuning does not improve accuracy?
Welcome! You haven't given us enough information to be able to diagnose this issue completely, but you should check your grid search code to see how each cross-validated model is being trained and note which parameters are different from those used with the 92% model. 

If it has something to do with the unbalanced data, it's because you're not stratifying your sampling of the dataset with respect to the labels (making sure training and validation sets have the same ratio of classes (in this case, 38% survive, 62% don't survive.))

I would guess that something is going on with your cross validation process.  If I had to guess specifics (and again, we can't say for sure given what you've posted here) , I would say that something you're doing in the CV probably results in those models not using as much training data as the 92% model.