[Izkata]

> The myth of data scientists as notebook jockeys is just one more symptom of the denial of SRE orgs to admit ML engineers are great system engineers

It's most obvious with this statement, but overall you seem to think "ML engineer == data scientist", which just isn't the case.

[mlthoughts2018]

That sounds like a No True Scotsman fallacy to me. You’re trying to define “data scientist” as someone who only knows how to use notebooks, fails to put testing as a first class consideration, etc., but that’s a severe minority of people with the job title of Data Scientist.

I manage teams of both ML engineers and Data Scientists and have designed hiring processes for both within large ecommerce companies for years.

[Izkata]

> You’re trying to define “data scientist” as someone who only knows how to use notebooks

I'm not the other person, and that is definitely not what I'm saying. There can be overlap, but the distinction is important: Data scientists use tools for analysis, ML engineers are capable of building those tools.

For example, the tool I'm aware of that some of our data scientists use is SPSS - but they have no programming experience, and could not remotely be grouped in with "ML engineers".

[mlthoughts2018]

I understand, I’m just saying that the “SPSS only” type of data scientist (glorified business analyst) you describe is very rare in industry and it’s not a useful broad brush to paint the field of data science with - it’s a greatly exaggerated and overrepresented stereotype.