In our digitized world, we are in dire need of people who make sense of the ever-increasing volume of data to improve our business strategies, policies and ultimately our lives and society as a whole. This is a daunting task, as - contrary to popular belief - numbers don't speak for themselves; they are the product of the social world we inhabit. In this sense, people who can crunch the numbers or are proficient coders are essential to this undertaking, but they only take you halfway there.

 

As a social scientist and data scientist, I can bring my knowledge on statistical modeling to the table, combined with a keen awareness of how we can (or can't) translate the model's output to actionable insights. After all, the road to data-driven decision making is laid with erroneous statistical reasoning.

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This doesn't mean we should shy away from learning from our data. On the contrary, what we really should fear is an overconfidence in the algorithmic black box or being blinded by complex-looking code. It's what led us to the housing bubble of 2008, to an overconfident presidential candidate in 2016 and to the biased and broken algorithms that shape our lives and limit opportunities for the downtrodden to this day. 

 

I believe this is still the forgotten calling of the social scientist in the 21st century: to serve as a sparring partner for the statistician and computer scientist. And as a teacher, there's nothing I like more than making people interested in all the exciting ways data can be leveraged to increase our understanding of social reality. So let's build that bridge; because if data is the new oil, we sure don't want to let it go to waste.