It is important to get comfortable dealing with data as a data scientist. One might have done a PhD and have learnt many statistical techniques.

HOWEVER: Given a problem, first try to think how you can solve the problem – Data Science or no data science.

Try to spend time visualizing data in a different ways, understanding the various attributes in the data. Check if the data is noisy, incomplete and so on. If needed clean the data.

Then, try to think : What is the simplest algorithm to try solve this problem. Ideally you first implement this. Very often, there is no need for ML in this step.

Then, Figure out what the problem with this simple approach is – solve using more complex statistical techniques as required.