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Data Scientists are a hot commodity, particularly as data changes the way that many companies do business. While it's cooled down since I finished grad school a few years ago, demand still far outstrips supply, and hiring Data Scientists (and getting hired) can be a Herculean task.
In a previous role, I was fortunate to have lead or supervised over 200 interviews, building a team from 2 to 85 people over the course of a year and a half. While this hyper-growth will probably be unique in my career (as it should be), I've picked up a few things about selecting and supporting Data Science talent.
Brendan Herger enjoys bridging the gap between data science and engineering, to build and deploy data products. Brendan is a Senior Data Scientist at Metis.
Brendan brings a unique combination of machine learning, deep learning, and software engineering skills. In his previous work at Capital One and startups, he has built authorization fraud, insider threat, and legal discovery automation platforms. In each of these cases he's lead a team of data scientists and data engineers to enable and elevate his client's business workflow (and capture some amazing data).
When he's not knee deep in a code base, Brendan can be found traveling, sharing his collection of Japanese teas, and playing board games with his partner in Seattle.
Metis (thisismetis.com) accelerates careers in data science by providing full-time immersive bootcamps, evening part-time professional development courses, online resources, and corporate programs based in Seattle, New York, Chicago, and San Francisco.
Brought to you by Kaplan, Metis focuses primarily on Python, machine learning, data visualization, deep learning, big data processing, statistical foundations, and more. Students and alumni of the bootcamp program receive continuous support from our career advisors, empowering them to pursue a successful career in the fast-growing field of data science.
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