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Comment on Data scientists shouldn’t need to know Kubernetesparent

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Agree thar work ethic is the most important thing since complicated qualitative things cannot be measured, trust precedes everything. But work ethic does not complete the puzzle because people dont know always what they dont know.

For the example you mentioned, I will use a simplification I make to explain levels of expertise of challenging knowledge: 1.ABOUT: Know about something (heard it, know some examples) 2. KNOW: Know that something well (I now understand it and can leverage it towards an end to end a useful thing, also know its weaknesses) 3. HUMBLE: Realize I did not know many things about it but now know many ways of using it, can correct and extend other people's work, most of the time. 4. EXPERT: Know why it was structured that way. Contribute to the knowledge/tool itself.

So for that PhD an initial estimate would be a 3 or 4 scale on the math level, 1 or 2 on the kubernetes level (don't know him ofcourse I can be wrong without first discussing). If he works independently level 2 kubernetes is pretty great. If he needs to be part of a larger support team, a level 3 knowledge based on my (admittedly back of the napkin and ambiguous) categorization might prove to be less risky.

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