zlacker

I have to work with code written by Data Scientists very often and, coming from a classical SWE background, I would not call what the average Data Scientist does full stack software engineering. The code quality is almost always bad.

This is not to take away from the amazing things that they do - The code they produce often does highly quantitative things beyond my understanding. Nonetheless it falls to engineers to package it and fit it into a larger software architecture and the avg. Data Science career path just does not seem to confer the skills necessary for this.

>>rcbdev+(OP)
For me, anecdotally, it was moreso the arrogance that was a major putoff. When I was a junior SWE I knew I sucked, and tried as hard as I could to learn from much more experienced developers. Many senior developers mentored me, I was never arrogant. Many data scientists on the other hand are extremely arrogant. They often treat SWE and DevOps as beneath them, like servants.

>>rcbdev+(OP)
I see a lot of work done by data scientists and a lot of work done by what I would call “data science flavoured software engineers”. I’ll take the SWE kind any day of the week. Most (not all, of course!) data scientists have an old school “it works on my machine” mentality that just doesn’t cut it when it comes to modern multi-disciplinary teaming. DVCS is the exception rather than the rule. They rarely want to use PMs or UI/UX, and the quality of the software is not (typically) up to production grade. They’re often blinding smart, there’s no doubt about that. But smart and wise are not the same thing.

>>rcbdev+(OP)
As an actual scientist, I would also not call what “data scientists” do “science”.