In his current role, Tom works to bring AI and Data Science solutions into utilities by focusing on the actionable use cases and insights that enable changes to business practices and produce measurable value from helping utilities adopt a data-driven approach to three key areas of their business: a customer-centric focus for getting maximum results and engagement on their portfolio of clean energy resources; reduced O&M costs, optimized capital expenditures, and improved reliability on their electric grid, gas pipeline, or water delivery systems; and enhanced vehicle mobility.

Prior to joining E Source Data Science, Tom led the Emerging Grid Technology team at Pacific Gas & Electric leading the implementation of new technology and analytics in support for PG&E’s Electric Operations as PG&E looked to reduce operational costs, improve safety, and increase reliability through a renewed focus on implementing a data-driven culture. Tom also built the “Grid of Things” team at PG&E, developing strategy and demonstrating new technology for the IoT of the electric grid– including DERMS, customer solar, battery storage, and other DER impacts to the changing grid. Tom has a BS in Electrical Engineering and an MBA, both from the University of Notre Dame.