Machine Learning Engineers, Data Scientists and their respective roles.

Over the past decade terms such as "Data Science", "Big Data", "Data Lake", "Machine Learning", "AI" and so forth have risen to the forefront (and sometimes fallen back again) of the everyday vocabulary used in the widest variety of industries. I do not wish to engage in an extended argument on consistent nomenclature, but there are two frequently used terms that are of particular interest to me: "Data Scientist" and "Machine Learning Engineer". In the broadest possible sense, both of these terms could be understood as referring to "technically skilled people who build machine learning solutions". "Data Scientist" is a term that over the years has become associated with a sort of generalist mathematician or statistician who can also code a bit and knows how to interpret and visualise data. More recently, the term "Machine Learning Engineer" has become associated with software developers who have picked up some mathematics along the way.