>Data Scientists, back in the day, were largely people with both a fairly strong quantitative background and a strong software engineering background. The kind of people who could build a demo LSTM in an afternoon.
As a field of "science" perhaps.
In real life (when it became hot) data scientists mostly meant "devs doing analytics" and a lot of it involved R and Python, or the term "big data" thrown around for 10GB logs, and things like Cassandra, with or without some background in math or statistics.
What it never has been, in practice, was a combination of strong math/statistics AND strong software engineering background. 99.9999% of the time it's one or the other.
As a field of "science" perhaps.
In real life (when it became hot) data scientists mostly meant "devs doing analytics" and a lot of it involved R and Python, or the term "big data" thrown around for 10GB logs, and things like Cassandra, with or without some background in math or statistics.
What it never has been, in practice, was a combination of strong math/statistics AND strong software engineering background. 99.9999% of the time it's one or the other.