[dzolob]

This happened to me when I left academia. No “real credentials”. Math expert with strong computer background (phd, published papers, years of experience in research/teaching) didn’t said more than “one year data science ‘masters’ abroad”. It took me quite some time to translate my expertise into marketable skills. Before that, I got passed on even for entry level positions.

[sjg007]

While a PhD can do the work, you really want the PhD to direct the work and explore new related things. A lot of this will depend on where you apply. That being said the market for data scientists has exploded in the past 2 years. 3-5 years ago things were different. Part of this is due to maturation of the tooling and the development of data platforms with organizations building out their data pipelines etc...

[endymi0n]

Thing is, while PhDs are usually by far the biggest domain experts you'll get, the absolute majority of them comes absolutely ill-equipped to lead anything, as university rarely teaches any skills in project, people or resource management skills, business sense, opportunity cost and presentation.

I've had disastrous outcomes going by credentials for leadership positions and these days only hire for demonstrated results on a real-world project.

Just my personal anecdotal evidence points me towards stellar academic success having a slight negative correlation with on-the-job performance. People who prefer building things with impact over citation rubber points usually don't survive in academia long enough for enduring a PhD.

[sjg007]

Like I said depends on the company.

[laichzeit0]

Well I had a “math expert” join my team recently and the problems were: they couldn’t work in a team, verbally expressed their intellectual superiority to everyone else, didn’t have the technical ability to get anything into production, could not follow instructions from superiors, thought most of the work they were given was “boring” and invented their own projects to work on, etc. I don’t know if that type of attitude is acceptable in academia, but it won’t work in industry. So now I’m extremely cautious about on boarding anyone without a proven track record at working outside academia. I simply don’t have the time to “manage” someone like that, shit had to get done.

[laurent92]

> thought most of the work was boring

It’s my biggest problem, both with people who want trendy frameworks, and myself who was bored with work in my younger years (til I started drinking and made changes and created my company). “From a million dollars, anything is your passion” is quite true (was it Joel on Software?), but IT is quite boring when evolving at the lower levels.

I’ve loved the book “Tribal leadership” which defines levels of career,

1-Almost dropout;

2-Bored worker (apathetic victim, but delivers work - This was me);

3-Working like an as but executing on your own skills (“lone warrior” - This is me now);

4-Executes well with a mentor above and mentoring below, which pushes the organization forward by “belonging” to the social fabric;

5-Executes for others - Creates relationship between people so they can execute together - that’s the “startup ecosystem” or corporate leader style, those people often look like gurus amazed by the smartness of people in their ecosystem, which, if they are contagious and humble, becomes true leadership.

[dzolob]

I believe these attitudes are somehow commonplace along academia, but I think it extrapolates to several disciplines, including software development or engineering.

There is a misunderstanding between where on the abstraction layer you are standing and how smart you are. The commonplace along mathematicians is that, as we are standing pretty low, we are the smartest of them all, and since there is basically no interaction with people in other layers, this belief gets comfortably reinforced.

Smarts comes in different flavors, and realizing that yours is just one of many and does not work at all in other contexts is hard. Treating others like morons and acting bored is a lousy way to deal with it.

[kybernetyk]

>didn’t have the technical ability to get anything into production

This is the biggest problem with fresh graduates.