Tom Martin works directly with clients on the execution of E Source data science. Prior to this role, Tom worked at PG&E, where he led the implementation of new technology and analytics in support of PG&E’s electric operations as the utility looked to reduce operational costs, improve safety, and increase reliability in support of grid modernization.
Tom Martin
Managing director, Data Science
Content by this author
Next-generation programs for an equitable clean-energy future
May 18, 2021
Join us in this webinar to learn how you can use a data-driven approach to build cost-effective programs that deliver on the vision of a clean-energy future.
Cut costs and improve grid reliability with data-driven vegetation management
November 23, 2020
Advances in technology and predictive data science are providing new opportunities for utilities to evaluate vegetation-management processes, achieve operational efficiencies, and save money. The E Source GridInform solution can help utilities calculate a vegetation risk score and plan next steps.
How to use predictive data science to plan for utility operations post-COVID-19
May 20, 2020
COVID-19 has affected every major industry around the world. For example, utilities have stopped shutoffs for nonpayment at least through May 31. No doubt a necessary act, but it will cause complications: a significant number of utility customers will be overdue on their bills in the next 24 months.