> VP level jobs are more about management skills than technical proficiency.
I would say this is true for all mid-management and up. Tech proficiency is largely irrelevant once you go into management.
I would say this is true for all mid-management and up. Tech proficiency is largely irrelevant once you go into management.
The lack of tech proficiency is even an advantage: in the companies where I worked, it is people who sucked badly at the technical job they had, who were moved to management, hoping that they might be less useless there. They are happy, they are paid twice as much as others who could fulfil their tasks, so it must mean they're good at something (something difficult to assess otherwise so money must be the right measurement). And then, since it is almost impossible to differentiate between a good and a bad manager, they could thrive a few decades going up in those roles, jumping from a company to another, boasting about the number of projects they 'made' (which are naturally more numerous than for the people who actually worked deeply on them).
You seem to be agreeing with me then. Of course you can be a bad VP Data Scientist without knowing anything about data science!
The job of a Data Science leader at a growing company is 50% recruiting and 50% sitting in planning meetings. Even if you started with good IC knowledge after a few years your skills will be rusty as hell. So assuming you know nothing and trusting your team and delegating is going to work infinitely better than trusting your own out of date skills.
edit: And yes, this is from personal knowledge, I've held such titles before and I've had a lot of offers for other such titles.
edit2: As a corollary, promoting someone to management just because they're a good IC is a really bad idea. You want your top ICs to stay ICs if possible. You want your managers to be people who actually can manage and want to manage.
Good scientific skills never go out of date. Being a good data scientist is not the same thing as knowing the big data framework du jour.
I accept that in many cases people with the job title 'data scientist' do not have any scientific skills, but that's a different matter.
This lies in stark contrast to the three other managers I've had for any length of time, who have all been considerably more technical and considerably less good at those other things. They've been able to step in and help fight fires in a way that the above manager couldn't have, but they haven't been as good at keeping their part of the organization running smoothly. Thing is, the latter is a manager's job, and the former isn't.
I mostly see management and implementation as orthogonal skills, with the caveat that experience is industry-specific in both cases.