This page will be devoted to resources for Mathematicians who would like to become Data Scientists in “The Industry”. This is not a page for people who are earning one of the new degrees in Data Science, though you may certainly find interesting things here. This page is primarily designed for the mathematicians who have a PhD (or most of one!) who are trying to figure out how to get from their pure or applied dissertation to a paying, industrial, data science position.

The mapping, *F*, between Academic life and Industry is not explicitly defined. Consider the sub-space of resumes which *F *maps between: the domain, a CV, to the range, LinkedIn is definitely non-continuous and occasionally nonsensical. And, how do you learn how to discuss your dissertation research in a way that a business can understand? What can you expect from your job if you become a Data Scientist? What does your work life look like? Is *F* invertible? I hope this page will be a resources that will improve your understand by at least epsilon.

Thoughts on the emotional journey:

- A Typical Day
- Deciding between Industry and Academics and …
- Some Industry Struggles: When Time > Brains
- Pie Chart of Emotions: Graduate School vs Industry

Thoughts and Articles about Data Science (Most recent on top):

- 150 DS and no business value: Great LinkedIn article by David Stephenson, Ph.D. about why businesses aren’t getting value from their data scientists.
- Data Science Insights: David Stephenson actually has a whole page dedicated to DS insights.
- Variations on Data Science: Social Mathematics introduction to the landscape of Data Scientists jobs in the US.
- How I became a Data Scientist Despite Having Been a Math Major: One man’s reflections on his journey between a math major and a year of graduate school to a data science role.
- Outside the Ivory Tower: Reflections on my own experience after a year and a half in industry.
- Data Science at SIAM conference: A wonderful page with lots of thoughts and ideas about what it means to do data science. Great resource.