Senior Quantitative Analyst, Commodities Pricing & Risk

NCSL International; Houston (TX); On-site; USD 100,000 - 300,000; Full time

Benefits offered by this job

Discretionary incentive eligible

Benefits

Job summary

Bank of America is seeking a Quantitative Analyst to join the Commodities Quantitative Strategies and Data Group. The role focuses on designing, implementing, and maintaining derivative pricing models and volatility tools used across the global commodities trading business.

The ideal candidate will have strong quantitative finance background, robust C++ and Python software development skills, and relevant experience with energy derivatives, volatility modelling or complex commodity products.

Qualifications

• Advanced degree in a quantitative field (MSc/PhD).
• Experience in pricing and modelling derivatives, preferably commodities.
• Strong knowledge of volatility modelling techniques and pricing theory.
• Proficiency in C++ and Python for numerical computing.

Responsibilities

• Develop, implement, and maintain pricing and risk models for commodities derivatives.
• Build pricing models for power, gas, and other energy derivatives.
• Design scalable pricing code and analytics platforms for risk analytics and trading needs.
• Collaborate with traders, risk managers, and structurers to deliver high‑performance analytics.
• Write production code in C++ and Python and modernize analytics infrastructure.
• Document models to support governance and regulatory requirements.
• Assist model validation and risk control teams through the lifecycle.

Skills

Derivatives pricing

Volatility modelling

C++

Python

Quantitative analytics

Communication skills

Education

MSc/PhD in quantitative field

Tools

Git

CI/CD

Linux

Job description

Bank of America is seeking a Quantitative Analyst to join the Commodities Quantitative Strategies and Data Group. The role focuses on designing, implementing, and maintaining derivative pricing models and volatility tools used across the global commodities trading business.

The ideal candidate will have strong quantitative finance background, robust C++ and Python software development skills, and relevant experience with energy derivatives, volatility modelling or complex commodity products.