Even people getting a quickie masters is hit/miss in my experience. At the end of the day, successful machine learning engineers require a whole suit of different skills, both technical, communicative, and even life skills that don't really exist for software devs. Not all those can be taught in 3 months, 2 years or even 6 years.

> both technical, communicative, and even life skills that don't really exist for software devs

Not a fan of this "data scientist is a unicorn" style of thinking. The best people in any profession (especially software engineering) also use these skills in their day-to-day work.

Data science isn't yet as stratified as software engineering, so there's less room for those without those "unicorn" skills. 10 years ago, there was no room at all. 10 years from now, there will probably be plenty of undergrads hired as junior data scientists.

Life skills? Communicative skills? What?

IMO essentially ML experts don't work in a bubble and may interface with potentially anyone at a company; C-level, engineering, product, marketing, ops, etc etc. What other tech-employee needs that flexibility? So, I grouped communication / life skills into being able to understand, read, interpret and ultimately provide value to potentially any team. Just having the technical skills will only get you so far.

Isn't this part of what most software engineering degrees teach though? Particularly surrounding project planning and requirements gathering?

I might be an outlier, but I interface with all of those on a daily basis in my role as a software engineer

IMO software engineering experts (leaders) need to do the same thing.

I agree with this comment. My experience has been that people don't really look at your resume unless you have machine learning experience on your resume or one of the stats type majors