Kyle comes to Level as a data scientist after finishing a math Ph.D. at Case Western Reserve University. Prior to that he worked for 6 years in biomedical engineering research using specialized MRI techniques to look at the connections in the brain. Kyle possesses the full range of data science skills from data cleaning and EDA to modeling and communication of results. He most enjoys translating cutting-edge machine learning techniques to (messy) real-world applications. He helps clients understand the value of their own data, draw insightful conclusions, and make data-driven decisions on how to proceed in the future. Much of his free time is (joyfully) taken up with his wife and 4 young children. He enjoys ongoing math research (especially into geometric/Clifford algebras), chess, and soccer when he gets time outside of family and work.
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