David Storey

David Storey

Associate Software Developer @ Auto-Owners Insurance

About David Storey

David Storey is an Associate Software Developer at Auto-Owners Insurance, specializing in parallel computing techniques for big data. He holds a Bachelor's degree in Mathematics from the University of Michigan-Dearborn and a PhD in Machine Learning from Michigan State University.

Work at Auto-Owners Insurance

David Storey has been employed at Auto-Owners Insurance as an Associate Software Developer since 2020. In this role, he focuses on utilizing parallel computing techniques to manage big data. His responsibilities include developing software solutions and enhancing data processing capabilities. Additionally, he is currently developing mainframe skills, including COBOL programming, CICS, and DB2, to support the company's operational needs.

Education and Expertise

David Storey holds a Bachelor's degree in Mathematics from the University of Michigan-Dearborn, where he studied from 2012 to 2016. He furthered his education at Michigan State University, earning a Doctor of Philosophy (PhD) in Machine Learning and Topology from 2017 to 2022. His academic background has equipped him with a strong foundation in mathematical principles and advanced machine learning techniques.

Background

Before joining Auto-Owners Insurance, David Storey gained valuable experience at Michigan State University. He served as a Research Assistant from 2019 to 2020 and as a Research Mentor for three months in 2018. Additionally, he worked as an Instructor of Business Calculus and Algebra during 2018 and 2019, respectively. These roles contributed to his teaching skills and deepened his understanding of complex mathematical concepts.

Machine Learning and Data Visualization Skills

David Storey has practical experience in machine learning, having reproduced results from several published research papers. He has applied machine learning algorithms to various datasets, including MNIST and IRIS. His technical skills include coding machine learning algorithms from scratch, such as SVM, K-NN, ANN, CNN, Decision Trees, and Random Forest. He is also experienced in creating static and interactive data visualizations using Python and Tableau.

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