This event will be Livestreamed:
Interviews suck. Interviews are an inefficient & biased way to determine & evaluate a person's skills & qualities, & data science interviews in particular tend to test for wrote memorization. Fortunately, interviews tend to cover a relatively small & standardized set of concepts, which makes it easy to brush up, & bring your A-game.
We'll cover a list of the concepts I use when leading interviews, have heard from colleagues, or have seen in the wild. I won't promise that this will land you your next job, but it should be a good place to start your review as you journey into the wild.
Brendan Herger enjoys bridging the gap between data science & engineering, to build & deploy data products. He is a Senior Data Scientist at Metis.
Brendan brings a unique combination of machine learning, deep learning, & software engineering skills. In his previous work at Capital One & startups, he has built authorization fraud, insider threat, & legal discovery automation platforms. In each of these cases he's lead a team of data scientists & data engineers to enable & 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, & 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, & corporate programs based in Seattle, New York, Chicago, & San Francisco.
Brought to you by Kaplan, Metis focuses primarily on Python, machine learning, data visualization, deep learning, big data processing, statistical foundations, & more. Students & 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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