Dan ShieblerHead of Machine Learning, Abnormal Security
Dan is the Head of Machine Learning at Abnormal Security, responsible for leading a team of 40+ detection and ML engineers in building the data processing and ML layers in the platform. Prior to Abnormal, Dan worked at Twitter, first as a staff machine learning engineer in Cortex, and later as the manager of the web ads machine learning team. Before Twitter, Dan worked as a senior data scientist at Truemotion, where he developed smartphone sensor algorithms to price car insurance. He has a PhD in machine learning from the University of Oxford.
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