Bachelor's degree in Quantitative Finance, Engineering, Mathematics, Statistics, Computer Science, Data Science, or a related quantitative discipline; Master's degree preferred.
3-7+ years of experience in US energy or commodity markets, focusing on quantitative risk analytics, structuring, and portfolio management.
Experience in electricity markets and familiarity with ISO markets such as PJM, NYISO, ISO-NE, or ERCOT preferred.
Proficiency in quantitative finance, risk analytics, time series forecasting, regression modeling, and machine learning techniques.
Strong programming skills in R, Python, SQL, and Excel, with experience in statistical modeling packages.
Responsibilities
Model the dynamics of an energy portfolio, including retail power sales contracts and renewable asset PPAs.
Develop and maintain stochastic simulation frameworks to quantify portfolio risk and expected financial outcomes.
Assist in identifying optimal hedge strategies to balance risk and profitability.
Support the calculation of risk metrics like Gross Margin at Risk (GMaR) and Value at Risk (VaR).
Evaluate profitability and risk characteristics of proposed customer transactions and provide recommendations.
Ensure models are documented, validated, and governed, improving data quality and analytics processes.
Develop scalable analytical tools and automated reporting solutions.
Benefits
Hybrid work model requiring 3 days per week in the New York City office.
Opportunities for professional development and continuous learning.
Access to advanced analytical tools and technologies.
Collaborative work environment with a focus on innovation.
Engagement in strategic decision-making processes within the energy sector.
Full Job Description
Overview
The Quantitative Portfolio Manager is responsible for developing, maintaining, enhancing, and utilizing quantitative models and tools to estimate and manage the risks embedded within the company's energy portfolio. This role supports Trading and Risk Management activities by delivering analyses related to price and volume risk, hedge effectiveness, asset optimization, and financial performance.
The successful candidate will combine strong quantitative, statistical, and programming skills with knowledge of energy markets to improve portfolio risk measurement and support strategic decision-making. The role will focus on modeling forward and spot prices, retail load, and structured transactions to quantify portfolio risk under various market conditions and evaluate hedge strategies.
This position is hybrid, requiring 3 days per week worked from our New York City office.
In this role, you will be involved with the following: Energy Portfolio Modeling
Model the dynamics of an energy portfolio composed principally of:
Retail power sales contracts
Power & gas hedges
Renewable asset PPAs
BESS
Heat rate call options
Environmental products
Ensure portfolio positions are accurately captured, reconciled, and represented in valuation and risk measurement processes.
Stochastic Modeling
Develop and maintain stochastic simulation frameworks to quantify portfolio risk and expected financial outcomes.
Calibrate correlated risk factor models to capture dependencies across portfolio exposures.
Model forward curve evolution and spot market dynamics based on fundamental and market-driven factors.
Analyze and forecast changes in retail customer composition, consumption patterns, and load characteristics.
Portfolio Hedging
Assist in identifying optimal hedge strategies to balance risk and profitability.
Evaluate hedge performance and effectiveness against portfolio objectives.
Analyze hedge costs and residual exposures.
Risk Analytics & Scenario Analysis
Support the calculation of risk metrics including:
Gross Margin at Risk (GMaR)
Value at Risk (VaR)
Expected Shortfall (ES)
Evaluate portfolio sensitivities and tail-risk exposures under a range of market and operational scenarios.
Develop tools that provide visibility into portfolio exposures and risk concentrations.
Market & Commercial Analytics
Support structuring activities through analytical modeling.
Evaluate profitability and risk characteristics of proposed customer transactions.
Provide recommendations regarding portfolio composition and risk mitigation opportunities.
Analyze regulatory and market structure changes affecting portfolio performance.
Data & Model Governance
Ensure models are appropriately documented, validated, and governed.
Improve data quality and analytics processes.
Develop scalable analytical tools and automated reporting solutions.
Maintain model transparency and audit readiness.
To be successful in this role, you are likely to have the following skills/experience: Education
Bachelor's degree in:
Quantitative Finance
Engineering
Mathematics
Statistics
Computer Science
Data Science
Related quantitative discipline
Master's degree preferred. Experience
3-7+ years of experience in US energy or commodity markets:
Quantitative risk analytics
Structuring
Portfolio management
Experience in electricity markets preferred.
Familiarity with ISO markets such as PJM, NYISO, ISO-NE, or ERCOT preferred.
Experience with portfolio risk measurement and calculation techniques.
Technical Skills: Quantitative & Statistical
Quantitative finance
Risk analytics
Time series forecasting
Regression modeling
Machine learning techniques
Monte Carlo simulation
Optimization methodologies
Forecasting methodologies
Programming & Analytics
Proficiency with:
R / Python
SQL
Excel
Experience with:
Statistical modeling packages
Energy Market Knowledge
Understanding of:
Forward and spot power markets
Load-following power sales
Energy hedging strategies
Environmental products (RECs, carbon products)
Load forecasting methodologies
Capacity markets
Ancillary Services
Key Competencies
Strong analytical and problem-solving skills
Ability to translate complex quantitative findings into business recommendations
Attention to detail and intellectual curiosity
Commercial mindset
Effective communication and presentation skills
Ability to work independently and manage competing priorities
