Virginie Montes
Portfolio Performance Engineer at ENGIE North America Inc.
Spring, Texas, United States
Summary
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Top SchoolVirginie Montes is a Portfolio Performance Engineer at ENGIE North America with a PhD in Physics and over a decade of quantitative experience applied across energy, trading, and astrophysics. She blends deep statistical and machine learning expertise—honed processing terabytes of multiwavelength astronomy data and publishing in the Astrophysical Journal—with production data engineering for solar generation and commodity trading pipelines. At 2DA Analytics she built anomaly detection, forecasting, and automated data-quality alerts on real-time ingestion systems using Python, AWS, ElasticSearch and Prophet, and now focuses on optimizing portfolio-level performance for utility-scale assets. Comfortable across the full analytics lifecycle, she moves models from research to post-deployment support and monitoring. Based in Spring, Texas, she brings a scientist’s rigor to operational problems, often surfacing subtle data-quality issues that materially impact forecasts. Her uncommon mix of astrophysics-grade signal processing and practical energy-domain product delivery makes her adept at extracting reliable signals from noisy, heterogeneous datasets.
7 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy - PhD Physics with dissertation in Astrophysics, Doctor of Philosophy - PhD Physics with dissertation in Astrophysics at New Mexico Institute of Mining and TechnologyMaster's degree Astonomy and Astrophysics, Master's degree Astonomy and Astrophysics at Université Paris Diderot - Observatoire de ParisBachelor's degree Physics, Bachelor's degree Physics at Université Paris Cité
French, English, SpanishGithub contributions (4)
virginiemontes/Astrophysics_Projects
Jun 2018 - Nov 2018
Contributions:31 commits, 26 pushes in 5 months
virginiemontes/Data_Science_Projects
Jun 2018 - Feb 2019
Contributions:34 pushes, 1 branch in 8 months
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