I know one hard science PhD who runs their own K8s cluster at home and plays with Linux distros.
That's super awesome for that data scientist, but the question for a business is can/should you structure yourself in such a way that you NEED employees with that cornercase level of joint expertise.
The answer is you really can't. Individuals have awesome strengths that they developed for reasons particular to them. Use those strengths when you can. But the business has to rely on a common denominator of a role or else it'll never fill it when their unicorn leaves to go backpacking in Europe.
Agree. You need to structure your talent pipeline, and organization, based on the average level of talent you can likely receive at your compensation bracket. You cannot create a single point of dependency on an employee who you'll never be able to replace for the same amount of money.
However, the issue is that productivity is logarithmic.
The unfortunate truth the school of hard knocks has shown me is that someone without the "roll your sleeves up" attitude to learn Docker is generally speaking just not going to be that effective when push comes to shove.
Now if you're using tools to abstract the time of data scientists who are CAPABLE of learning Docker, that is a different story.
But someone who starts grumbling about having to learn the command line to containerize their pipeline is generally speaking on the west side of the Pareto principle.
I can only guess at which particular area they will trip up, but it'll be somewhere.
Comments
That's super awesome for that data scientist, but the question for a business is can/should you structure yourself in such a way that you NEED employees with that cornercase level of joint expertise.
The answer is you really can't. Individuals have awesome strengths that they developed for reasons particular to them. Use those strengths when you can. But the business has to rely on a common denominator of a role or else it'll never fill it when their unicorn leaves to go backpacking in Europe.
Agree. You need to structure your talent pipeline, and organization, based on the average level of talent you can likely receive at your compensation bracket. You cannot create a single point of dependency on an employee who you'll never be able to replace for the same amount of money.
However, the issue is that productivity is logarithmic.
The unfortunate truth the school of hard knocks has shown me is that someone without the "roll your sleeves up" attitude to learn Docker is generally speaking just not going to be that effective when push comes to shove.
Now if you're using tools to abstract the time of data scientists who are CAPABLE of learning Docker, that is a different story.
But someone who starts grumbling about having to learn the command line to containerize their pipeline is generally speaking on the west side of the Pareto principle.
I can only guess at which particular area they will trip up, but it'll be somewhere.