Senior Quant Analyst - Energy Risk & Structuring (BESS)

Clearway Energy; San Francisco (CA); Hybrid; USD 140,000 - 178,000; Full time

Job summary

Clearway Energy seeks a Senior Associate in Risk and Structuring Analytics to develop quantitative models for BESS valuation, structured products pricing, gas generation optimization, and market analysis. You will build CWENQuant, implement VaR and MtM frameworks, and provide risk insights to inform trading, origination, development, and asset management.

Candidates should have a STEM degree and 3+ years in energy modeling, with Python, ML/DL, and optimization tools.

Qualifications

• Bachelor’s degree in Engineering, Finance, Math, Stats, Economics, or related field.
• 3+ years in energy sector modeling or quantitative roles.
• Experience building ML/DL models with scikit-learn, Keras, or TensorFlow.
• Proficiency in Python; strong data analysis skills.
• Knowledge of power markets (ISO CAISO/ERCOT) and BESS assets.

Responsibilities

• Develop complex optimization models for BESS dispatch, renewables, gas, and data center projects.
• Forecast prices using ML/DL based on load, gas, wind, and solar data.
• Maintain gas dispatch and toll pricing models; perform MtM and risk analytics.
• Build CWENQuant data pipelines and dashboards.
• Design MtM, VaR, and PaR frameworks for various positions.
• Run scenario and stress tests to quantify tail risk.
• Quantify hedge effectiveness and hedge adjustments.

Skills

Python programming

Machine learning

Quantitative modeling

Optimization modeling

Risk analytics

Communication skills

Team collaboration

Education

Bachelor’s degree in Engineering, Finance, Mathematics, Statistics, Economics, or related field

Tools

PuLP

Gurobi

CPLEX

scikit-learn

Keras

TensorFlow

CWENQuant

Job description

Clearway Energy seeks a Senior Associate in Risk and Structuring Analytics to develop quantitative models for BESS valuation, structured products pricing, gas generation optimization, and market analysis. You will build CWENQuant, implement VaR and MtM frameworks, and provide risk insights to inform trading, origination, development, and asset management.

Candidates should have a STEM degree and 3+ years in energy modeling, with Python, ML/DL, and optimization tools.