Quantitative Portfolio Manager

Quantitative Portfolio Manager

The future of energy is digitized, decarbonized and localized. At SmartestEnergy, we need revolutionary thinkers to help our customers make the most of this new landscape, thinking differently to find smart solutions to complex problems.

Formed in 2001, we're an agile business driven by entrepreneurial thinking. As a subsidiary of the Marubeni Corporation, we also have strong investment and infrastructure behind us. As well as our three offices in the US, we have three offices in the UK and another in Australia. Further expansion is planned for 2027 and beyond which means global career opportunities for you, with plenty of potential to explore new markets.

When you join our Team, you will have the opportunity to contribute and make an impact every single day.

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

Diversity

Celebrating our inclusive and diverse culture is core to what we do. We value everybody irrespective of race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability and genetic information (including family medical history). EOE.

We know that for our business to thrive we need diverse talent with a range of backgrounds, skills and capabilities in each of the countries in which we operate. We view diversity as one of the key enablers that helps our business to grow.

We are committed to the full inclusion of all qualified individuals. As such, if a reasonable accommodation is needed to participate in the job application or interview process, please reach out to the HR & People Team via email View email address on click.appcast.io so we can discuss with you further.