Diego Cerda is a Senior Data Science Associate at Good Energy Collective, where he leads advanced energy data analysis and applied research across clean energy systems. With an M.Sc. in Advanced Computer Science and over seven years of experience in the energy sector, Diego brings deep expertise in data science, machine learning, and energy systems modeling. At Good Energy Collective, his work focuses on supply chain modeling, reactor demand analysis, and quantitative assessments of energy system deployment, supporting evidence-based policy and planning for the clean energy transition.

‍

Prior to joining Good Energy Collective, Diego worked as a Performance Engineer, where he developed predictive models, monitoring systems, and analytics platforms for solar, wind, battery storage, EV charging infrastructure, and energy markets. His work supported large-scale energy deployments, improved system reliability, and enabled data-driven operational and planning decisions.

‍

At Good Energy Collective, Diego is responsible for energy data analysis, modeling, and research outputs that inform reports and public-facing insights. He is passionate about applying data-driven solutions to climate and energy challenges and aims to bridge technical analysis with real-world policy impact. When not working with data, Diego enjoys participating in hackathons, exploring new machine learning applications, and contributing to open-source projects.

‍