At The Data Incubator we run a free eight-week Data Science Fellowship Program to help our Fellows land industry jobs. We love Fellows with diverse academic backgrounds that go beyond what companies traditionally think of when hiring Data Scientists. Brendan was a Fellow in our Fall 2015 cohort who landed a job with one of our hiring partners, Jolata.
Tell us about your background. How did it set you up to be a great Data Scientist?
I did my PhD research in theoretical condensed matter physics at the University of California, Santa Barbara. The focus of my research was on studying the phase diagram of chains of non-abelian anyons. Because such chains are gapless in most regions of the phase diagram we had to model them using very large matrices in C++. To make this computation more tractable we used hash tables and sparse matrices. Besides my background in numerics I also took the time to learn Python, Pandas, SQL and MapReduce in Cloudera a few months before starting the fellowship.
What do you think you got out of The Data Incubator?
The Data Incubator gave me a solid foundation in data parsing, large scale data analysis and machine learning. I went into the fellowship already knowing about various concepts like SVM, bag-of-words and cross-validation. But I learned how tie these together into a elegant models that are both modular and easy to modify or upgrade. I also learned how to use Map Reduce on a cluster where the behavior of your program can be quite different then on a single node.
There’s little doubt that cloud computing will play an important role in data science for the foreseeable future. The flexible, scalable, on-demand computing power available is an important resource, and as a result, there’s a lot of competition between the providers of this service. Two of the biggest players in the space are 
