I lead a team of data scientists at Code for San Francisco’s Data Science Working Group and at an A.I.-based startup, and in my experience, those who are most likely to get a data science position are those who have a graduate degree in a physical science or in mathematics. There are two overarching reasons for this…

1. Popular assumptions over quantitative aptitude: It’s ironic, but for many physical sciences, Statistical Inference is not a part of their core curriculum, while it is a part of the core curriculum of most -if not, all- social sciences (all we have to work from is probability, given the black box nature of the mind). Still, most of us associate various maths solely with the physical sciences. What’s more, those who work in the physical sciences have rarely been exposed to the actual scientific rigor of the social sciences, either in school or at work. Indeed, I’ve personally witnessed a number of physical scientists consider the social sciences synonymous with the arts or humanities, which is supremely tragic, professionally speaking.

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