Data Scientist vs Machine Learning Engineer
Does anyone else agree that Machine Learning (Engineer) should be its own job title separate from "Data Scientist"? DS encompasses many low-level techniques which can be (and often are) executed by engineers without any of the mathematical pillars required for proficient machine learning.
Agreed, job titles are very ambiguous in my opinion
actually Amazon has these roles. ML engineer, BIE (commonly given data scientist business title), applied scientist and research scientist. expected skills are different for each.
Facebook also does this...exception to the rule?
I suspect companies large enough to require specialization do this. e.g. we also have economists, statisticians, and within the applied science role, you'd find people specialized in ML, OR, etc (though these don't have their own roles).
Machine learning isn't a good enough stand-alone buzz word yet. Let's wait a bit longer while deep learning grows up.
I'm only vaguely familiar with data science in practice, but I have a hard time believing that one educational background is enough to be successful. Half of the books are extremely high level math and hand-wavy, the other half are extremely practical and devoid of theory. I had associated scientist with the math side and engineer with the practical side. It seems like these would rarely be the same person, but both would be necessary.
you actually have that backward. DS is generally less math and more practice, where MLE is generally involved in the algorithms from a theoretical standpoint all the way thru to implementation
Yes, and eventually CS graduates will realize it and that is the day it gets separated.