How wide is the gap between a MLE and a data scientist?

Hi! I’m currently switching from a postdoc in academia to a data scientists in the industry. I wish to finally be an MLE after some time, and I’m wondering how wide is the gap between a normal data scientist and an MLE? And what skills do I need to pick up in order to accomplish the transition? (By “data scientist” I mean someone adopting statistical models to make predictions, not just making business analytics)

I have a strong quantitative background, numerous experiences of building and using numerical models based on physical theories (as opposed to statistical ones) to solve problems, and some experience using machine learning models to make predictions. My strength lies in understanding the algo (including math) behind each model, while I’m not that good at coding from a software development perspective.

This question was answered during the session in minute 36:41