Mathematics in data science? (Thinkful blog post)

I was recently quoted in a blog post about the math needed to succeed in Thinkful’s data science bootcamp:

In the post, I mention some of the foundational math topics that are needed as a beginning data scientist, as well as how Thinkful helps you get there.

I also explained in the post how our emphasis on Thinkful is on using these mathematics tools for real business application. This is really where the rubber meets the road for data scientists and I wanted to elaborate on this relationship between mathematics, data science and ultimately business.

Methods are not stories

Data scientists use math as a way to make sense of the world, and particularly their business. The math is a useful representation of reality. It’s important to remember that it’s your world… the math is just living in it.

Data scientists excel in mathematical models but these are, in the end, models. It’s important not to take them out of the context of their business use — this is why domain expertise is a legitimate domain of data science.

Humans are natural storytellers and make sense of their world with stories, so data scientists do well to remember that their mathematical models are not the same as the stories which their audience use to make sense of their lives.

There’s more to science than math

Data science is a mathematically sophisticated discipline, but don’t make too much of it: remember that the operating principle of data science is, well, science.

Mathematics is the “queen of the sciences,” but that just means that it, too, is only a science.

Again here, mathematical methods are just a tool for inquiry. Complex mathematics can indeed lead to more advanced science, but only if done in the context of a valid scientific workflow.

It’s your world, the math is just living in it

In the above video, I claimed that fear of math is probably leading many potentially great data scientists away from the field. This is too bad: it’s important not to take the rightfully prominent position of mathematics out of the overall context of data science.