Data are becoming the new raw material of business
The Economist

Machine Learning and Modeling the Stock Market: Alumni Spotlight on Michael Skarlinski

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. Michael was a Fellow in our Winter 2016 cohort who landed a job with one of our hiring partners, Schireson Associates


Tell us about your background. How did it set you up to be a great Data Scientist?

My PhD work was in computational materials science, where I worked with reactive molecular dynamics simulations. The field is totally simulation based, and typically requires high performance computing resources. Running these simulations helped build my chops for working with parallel systems and command line tools. The software required familiarity with some powerful languages and APIs like C and CUDA. Learning those definitely helped my understanding of Python once I converted to using it.

Toward the third year of my PhD I got really interested in machine learning. I started using scikit-learn to predict different aspects of simulations I worked on. These projects became a large part of my thesis and contributed to choosing The Data Incubator as a next step in my career.


What do you think you got out of The Data Incubator?

The experience and camaraderie of trying to complete weekly projects with my peers was the highlight of my time at The Data Incubator. Everyone had expertise in different areas, and I learned a ton just from interacting with the other fellows. The instructors and daily lessons exposed me to concepts and data-tricks which hadn’t been on my radar. Honestly, most of the reviewed concepts were brought up in interviews and I’m seeing them again in my job.

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