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.
Cartoons about 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):
- Resume as a Cover Photo: How to make your resume stand out and look good.
- Leaving Academics: My own 5 year reflection on why it feels so hard to leave Academics.
- Marketing Academic Strengths in Industry: Social Math view on finding your sentence
- 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.
- 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.
- Triple Threats: Social Math post on how to make DS work in corporate setting.
How to make the transition from Academics to Industry:
This is something I’m asked about fairly often, so I’m going to compile a small list of resources here.
- 10 Things Smart PhDs do NOT Put on their Industry Resumes: A really clear summary of the first steps towards making your Industrial resume.
- 5 Articles to help you make a great LinkedIn Profile: Another article from CheekyPhd.
- How to sail smoothly from Academics to Industry: Nature Article of the subject. Pretty high level.
