Energy Analyst (Staff Sr Staff)

Description

• Own the end-to-end analytical engine that drives Equilibrium’s AI operating system for the power sector. You will translate terabytes of grid, weather, load, and market data into actionable insights that directly shape trading, hedging, and asset-optimization decisions worth hundreds of millions of dollars.
• Architect, validate, and continuously refine forecasting models for electricity demand, renewable generation, congestion, and price formation across ISOs/RTOs (ERCOT, PJM, CAISO, MISO, SPP). Your models will run in real time, ingest live SCADA feeds, satellite imagery, and numerical weather prediction ensembles, and must deliver sub-hour accuracy under strict latency budgets.
• Partner with power-market economists, meteorologists, and grid operators to translate physical constraints—transmission limits, ramp rates, ancillary-service requirements—into probabilistic constraints inside our optimization layer. You will surface these insights through intuitive dashboards and APIs consumed by traders, risk managers, and origination teams.
• Lead scenario analysis for long-term resource-adequacy studies, capacity-expansion pathways, and policy-impact assessments (IRA tax credits, state RPS, FERC Order 2222). Your work will inform multi-gigawatt renewable-storage hybrid investments and shape the firm’s view on forward curves 5–20 years out.
• Design and maintain automated data-quality pipelines that detect anomalies in ISO bids, metered load, and nodal prices within minutes, not hours. You will implement statistical tests, ML-based outlier detection, and human-in-the-loop review workflows to ensure every downstream model consumes clean, trustworthy data.
• Drive the integration of satellite-derived irradiance, wind-speed, and snow-cover data into short-term renewable forecasts. You will benchmark public datasets (NOAA HRRR, ECMWF, Copernicus) against proprietary drone and LiDAR collections to squeeze every last megawatt of accuracy from our solar and wind fleets.
• Build and deploy containerized Python services on AWS (EKS, Lambda, Fargate) using Infrastructure-as-Code (Terraform). You will set up CI/CD pipelines with automated unit, integration, and shadow-trading tests so that every model update can be safely promoted to production in under 30 minutes.
• Present findings to the executive committee, investors, and external stakeholders in quarterly deep-dives. You will translate complex stochastic forecasts into clear narratives that explain risk-adjusted P&L, Value-at-Risk, and carbon-abatement metrics.
• Mentor junior analysts and data scientists, codifying best practices for feature engineering, cross-validation, and back-testing. You will foster a culture of reproducible research by enforcing Git-based workflows, peer code review, and comprehensive documentation.
• Stay ahead of the regulatory curve—track FERC, NERC, and state-level rule changes; quantify their impact on nodal pricing volatility; and rapidly prototype new model components that keep Equilibrium at the forefront of market design evolution.

Requirements

• 4+ years of quantitative energy-economics or power-market analysis, including hands-on experience with nodal pricing, LMP decomposition, and FTR/CRR valuation
• Expert-level Python (pandas, NumPy, xarray, scikit-learn, PyTorch) and SQL; ability to write performant vectorized code that scales to 100 GB+ datasets
• Deep familiarity with at least two major ISO market structures (ERCOT, PJM, CAISO, MISO, SPP) and their respective bidding, settlement, and congestion mechanisms
• Nice-to-have: PhD or MS in Operations Research, Electrical Engineering, Atmospheric Science, or related quantitative discipline; experience with cloud-native MLOps (Kubernetes, Airflow, MLflow); track record publishing or presenting at IEEE PES, CIGRE, or Energy Analytics conferences

️ Benefits

• Fully remote-first culture with quarterly in-person summits in destinations like Tahoe, Lisbon, or Kyoto—travel and lodging covered
• Competitive base salary plus annual performance bonus tied to fund-level P&L and carbon-reduction KPIs
• Equity participation in a high-growth climate-tech company backed by Breakthrough Energy Ventures and leading infrastructure funds
• 100 % employer-paid medical, dental, vision for you and dependents; mental-health and fertility support via Carrot and Modern Health
• $3,000 annual learning stipend for courses, conferences, or certifications (CFA, FRM, AWS ML) plus paid volunteer time for climate-advocacy nonprofits

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