Trevor Stanley is a Senior Analytics Engineer with eight years of experience building data-driven tools and models for the energy sector, currently advancing analytics and reporting at The AES Corporation. He blends data engineering, predictive modeling, and energy economics—skills honed at NREL and Ascend Analytics—to optimize decision-making for energy trading, DERs, and battery valuation. Trevor brings full-stack data tooling experience (Python, PostgreSQL, Docker, AWS, Julia) and a track record of improving computational efficiency and situational awareness through thoughtful software design and visualization. His background spans government-funded research, energy tech commercialization, and a DoD-backed cybersecurity IoT accelerator, reflecting both domain depth and cross-disciplinary problem solving. Based in San Francisco, he pairs rigorous academic training (summa cum laude in Computer Science & Environmental Science) with practical industry impact at the intersection of government, energy, and emerging tech.
8 years of coding experience
5 years of employment as a software developer
Minor, Geographic Information Science and Cartography, Minor, Geographic Information Science and Cartography at University of Colorado Boulder
The Distributed Generation Market Demand (dGen) model simulates customer adoption of distributed energy resources (DERs) for residential, commercial, and industrial entities in the United States and other countries.
Contributions:1 release, 9 commits, 6 PRs in 1 year 3 months
Contributions:33 commits, 30 pushes, 1 branch in 3 years 6 months
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