18 Reasons Data Scientists are Difficult to Manage

Of course each data scientist is different, so please take this criticism with a grain of salt. By a long stretch, they don't apply to all data scientists.

Reasons:

Data scientists are creative and bring disruptive IP (intellectual property), and this can cause havoc for their company.
They can steal and leverage your IP, and create IP leaks.
Are not great communicators, and sometimes can be stubborn
Work on stuff that they like, even if it does not translate in yield, or if it is not stuff they are paid to do
Hate doing mundane work, and are bad at it
Have more career options than many employees, and are thus difficult to retain
Don't like team work,
Tend to be elitist and isolationist
Are sometimes very attached to a specific technology and don't want to try something different (they sometimes give the impression that they haven't realized the world is evolving without them)
Are not good listeners
Work for you just to save enough money to launch their company and compete with you in a couple of years
Are arrogant: bad impact on teams
Think sales, marketing and executives are stupid
Can do real nasty stuff if they become a disgruntled employee
Are sometimes reluctant to share their knowledge, train colleagues, or outsource to colleagues
Are not great at prioritizing
Are not great at switching (on-demand) from one task (coding) to another (presenting)
Sometimes have issues working with women (especially managing or being managed by women), especially if coming from a male-dominant culture