Cameron McBride (Rubicon Project)
Data science continues to explode as a field as the industrial need for scientific rigor grows. It can be referred to by many names: machine learning, artificial intelligence, statistics, science, or sometimes even software engineering. I trained to be an academic scientist, and did research in extragalactic astronomy and cosmology across four major research institutions and as part of an international collaboration. Over the past three years, I have worked for two startups and a larger corporation solving challenging problems across two fields. Skills I learned analyzing galaxy distributions were put to use in refining algorithms to better predict a shopper’s size of clothing in online sales and optimizing the massive flow of information in real time bidding systems. In this talk, I will candidly discuss my experience and key learnings of building a new career. With some practical descriptions of the problems I worked on, I will convey what skills I found invaluable, and what notions I found to be misguided. My story is not unique. Many scientists consider careers in industry, and all scientists collaborate with or advise people who go into these fields. It goes both ways as many tools being refined in industry are being increasingly applied to academic analyses. Adapting to this “Age of Data” is changing the very nature of the communities, funding structures, and the practical toolsets we all use everyday.