Dr. J. Andrew Howe

Dr. J. Andrew Howe has a diverse work experience in the field of data science and research. Dr. J. Andrew currently works at Wood Mackenzie as the Director of Data Science, where they lead the development of data engineering pipelines and machine learning models. Dr. J. Andrew also manages the Analytics Lab team and guides skill development efforts. Prior to this, they worked at Acadamia as an Independent Researcher, focusing on robust model selection, information complexity, and statistical computing. Dr. J. Andrew also served as an Energy Research Fellow at KAPSARC, conducting impactful research on global energy usage and guiding the development of an open data science technology platform. Dr. Howe also has experience as a Founding Partner and Consultant/Trainer at Risk Dynamics Consultancy, where they provided risk modeling and risk management services. Additionally, they have held roles as an Executive Editor at the European Journal of Pure and Applied Mathematics, a Manager in Market Management/Customer Experience at Allianz Türkiye, a Decision Risk Modeling Consultant at Palisade Corporation, and a Manager of Data Architecture, Reporting, and Analytics at TransAtlantic Petroleum Ltd. Dr. J. Andrew also worked as a Specialist in Energy Market Strategy at the Tennessee Valley Authority and as a Teaching Assistant at the University of Tennessee, where they instructed students and engaged in statistical research.

Dr. J. Andrew Howe has a PhD in Statistics from the Haslam College of Business at the University of Tennessee, obtained from 2005 to 2009. Dr. J. Andrew also has an MS in Statistics from the same institution, which they completed from 2005 to 2007. Prior to that, they earned an MBA in Finance from the Keller Graduate School of Management of DeVry University from 2000 to 2002. Their undergraduate degree is a BS in Pure & Applied Mathematics and Physics from California Baptist University, earned from 1993 to 1997. Additionally, Dr. Howe has obtained various certifications in areas such as Agile development, deep learning, Apache Spark, and statistical analysis.