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Is is because data work doesn't need a degree and the degree holders don't want to risk their career for doing something that is off topic to their degree?
by totorovirus 6y ago
Is is because data work doesn't need a degree and the degree holders don't want to risk their career for doing something that is off topic to their degree?
- js8 6y agoIt's the other way around. Data work does require understanding of the domain, and degree holders don't want to risk their career for doing something that is off topic to their degree, that is, learning the domain. I am just pointing out the your statement has an other side, too. It's kinda like with programming languages, people think that particular programming language, rather than domain details, are the transferable skill for SW developer. In data science, it's the statistical modelling theory that is considered to be the transferable skill, rather than the business domain. But you always need both, and there is no particular reason why would, in hiring, one prefer knowledge of the tooling to knowledge of the domain. It just happens to be, as a kind of spontaneous symmetry breaking.
- vinay_ys 6y agoFor a strong engineer today, the most valuable/transferable skills are ability to learn new things (in both tech and domain) and effective problem-solving (in different settings). Such an engineer can learn the most important aspects of statistical modeling needed for their problem at hand. The kind of researchers who are averse – "to getting their hands dirty" – to do data tasks will have a hard time staying relevant in any production setting. Unless the company has dedicated research department which is a million miles away from product teams, they are going to have a tough time being impactful.