Build and run electric grid models to analyze transmission behavior, nodal pricing, congestion drivers, and long‑term grid dynamics.
Contribute across the entire modeling stack—including power flow, production cost modeling (PCM), and capacity expansion modeling (CEM).
Data Science & Applied Research
Ingest, clean, and analyze large and noisy datasets from APIs and structured markets data sources.
Apply machine learning and statistical modeling for forecasting, pattern detection, anomaly detection, and power market insights.
Validate results using engineering intuition, historical behavior, and known system constraints.
Model Development & Workflow Automation
Build curated datasets for grid topology, outages, line ratings, and operational assumptions.
Develop end‑to‑end modeling workflows as an internal “product”—from data ingestion to QA to delivering insights on congestion, basis risk, nodal price impacts, and asset value.
Collaboration & Innovation
Translate macro‑grid trends—renewables growth, electrification, weather impacts—into quantitative metrics used by commercial and strategy teams.
Collaborate with national labs, startups, consulting partners, and internal global research teams.
Support testing and technology transfer for external tools and internal research platforms.
Profil du candidat 🎓 What You Bring Minimum Qualifications
Bachelor’s degree in Electrical Engineering, Power Systems, Energy Systems, Applied Math, Computer Science, or related field.
5+ years of experience in transmission modeling, power system analysis, electricity markets, or similar analytical work (utility, ISO/RTO, consulting, analytics).
Hands‑on experience in major U.S. ISO/RTO nodal markets (ERCOT, PJM, CAISO).
Strong proficiency in Python and data science libraries.
Demonstrated experience using data analytics or ML to extract market insights from large datasets.
Preferred
Graduate degree (M.S./Ph.D.) in Power Systems or related field.
Familiarity with production cost modeling (e.g., PLEXOS).
Experience linking power flow, congestion analysis, PCM, or CEM models.