There are many opportunities in industry which are open to mathematicians, but knowing where to look can be a challenge for those with a primarily theoretical background. To industry professionals, one major appeal of hiring mathematicians of any background is our ability to adapt to a wide range of problems. This summer I participated in multiple internships working in data science and machine learning, despite having minimal prior experience.
The first part of this talk is aimed at graduate students who may be interested in applying to similar internships. I will discuss how I searched for opportunities and what it was like to transition from proof-based mathematics to work in an industry setting. In the second part of this talk, I will discuss my work with a startup company and how we applied machine learning techniques to detect, distinguish, and evaluate different poses in fitness exercises.