Probabilities in KERAS
Try predicting log-probabilities that would give you bigger seperation (i.e. values between -inf and 0) I Would clip these values (so that you dont take log from 0 which would be -inf but something like if 0 than log(0.0001)
For example:

y_pred = estimator.predict_proba(X.drop(columns=self.drop_columns))
log_prob = lambda x: np.log(np.clip(x, 0.001, 0.999)).reshape(-1, 1)
y_pred = np.hstack([log_prob(y_pred[:, 0]), log_prob(y_pred[:, 1])])