Quantitative Analyst

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Regular Full-Time Professional National Service Center - Carmel, Carmel, IN, US

This position will be responsible for the development, maintenance, and enhancement of portfolio optimization and risk models. Additionally, the analyst will interact with our clients to identify portfolio risk exposures and assist in the evaluation of hedging strategies that support business objectives. This role requires strong organization and prioritization skills, a problem‑solving mindset, and the ability to apply best quantitative practices to provide meaningful insights.

• Candidate will be responsible for quantitative analysis to assist clients with the management of physical, financial, and market risk exposures.
• Builds and maintains stochastic energy portfolio optimization models.
• Provides scheduled and ad-hoc reports to clients and senior management with detailed analysis of portfolio cost, hedge position, and risk metrics.
• Assists in the evaluation of hedging strategies, structured transactions, and long‑term asset developments.
• Communicate with clients to understand and address new and ongoing analytical needs.
• Collaborates within and across teams to share and manage data and to innovate data solutions.
• Ability to travel.
• Will adhere to all ACES corporate policies and comply with all ACES regulatory requirements, including but not limited to NERC, FERC, and relevant state regulations, as applicable to this position.
• Any additional responsibilities assigned by management.

• Bachelor’s degree or higher in mathematics, economics, finance, computer science, or an appropriate discipline.
• Experience in quantitative study, in finance, or the energy industry such as system operations, trading, and asset structuring.
• Minimum of 1 year of experience.
• Knowledge of ISO/RTO markets and industry fundamentals such as operating procedures, buying and selling of energy, asset valuations, and position management.
• Foundational understanding of statistics, mathematics, and finance.
• High degree of analytical and technical skills, with the ability to organize and interpret data and to use complex models.
• Experience in applicable programming languages such as R, SQL, and Python preferred.
• Experience in Microsoft Excel.
• Excellent written and oral communication skills.