being a good data scientist is about having enough intuition about the dataset to ask the right question aka form the hypothesis.

working out the question is what makes it a hard(and creative) process, and then you can apply your ML toolbox.

edit: whats different from a data scientist vs analyst/statistican is they build their own tools as the datasets are too massive & non-standard for the usual toolset.