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The Role of the Social Scientist in Data Science


15 March 2014

The Role of the Social Scientist in Data Science

Both LinkedIn and Facebook are social network companies. Oftentimes a description or definition of data scientist includes hybrid statistician, software engineer, and social scientist. This made sense in the context of companies where the product was a social product and still makes sense when we’re dealing with human or user behavior. But if you think about Drew Conway’s Venn diagram, data science problems cross disciplines—that’s what the substantive expertise is referring to.

In other words, it depends on the context of the problems you’re trying to solve. If they’re social science-y problems like friend recommendations or people you know or user segmentation, then by all means, bring on the social scientist! Social scientists also do tend to be good question askers and have other good investigative qualities, so a social scientist who also has the quantitative and programming chops makes a great data scientist.

But it’s almost a “historical” (historical is in quotes because 2008 isn’t that long ago) artifact to limit your conception of a data scientist to someone who works only with online user behavior data. There’s another emerging field out there called computational social sciences, which could be thought of as a subset of data science.


[1] Rachel Schutt and Cathy O’Neil, Doing Data Science, O’Reilly Media, Inc., 2014.

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