Commodities Quantitative Analyst

Job Description:

At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day.

Being a Great Place to Work is core to how we drive Responsible Growth. This includes our commitment to being an inclusive workplace, attracting and developing exceptional talent, supporting our teammates’ physical, emotional, and financial wellness, recognizing and rewarding performance, and how we make an impact in the communities we serve.

Bank of America is committed to an in-office culture with specific requirements for office-based attendance and which allows for an appropriate level of flexibility for our teammates and businesses based on role-specific considerations.

At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!

Job Description:
This job is responsible for conducting quantitative analytics and modeling projects for specific business units or risk types. Key responsibilities include developing new models, analytic processes, or systems approaches, creating technical documentation for related activities, and working with Technology staff in the design of systems to run models developed. Job expectations include having a broad knowledge of financial markets and products.

We are seeking a talented and driven Quantitative Analyst to join our Commodities Quantitative Strategies and Data Group (QSDG). This mid-to-senior level role focuses on the design, implementation, and maintenance of cutting-edge derivative pricing models and volatility modelling tools used across our global commodities trading business. The ideal candidate will have a strong background in quantitative finance, robust software development skills in both C++ and Python, and prior experience working on derivatives pricing models — ideally within commodities, though experience in FX, equities, or other asset classes with complex volatility dynamics is also relevant.

Key Responsibilities:

• Develop, implement, and maintain pricing and risk models for a wide range of commodities derivatives.
• Contribute to the design and calibration of volatility surfaces and models.
• Design and build scalable model pricing code and quantitative software platforms that support risk analytics and trading needs.
• Work closely with traders, structurers, and risk managers to deliver high-performance analytics and model-driven tools.
• Write high-quality production code in C++ and Python, and contribute to the ongoing modernization of the analytics infrastructure.
• Write comprehensive model documentation to support internal governance and regulatory requirements.
• Collaborate with model validation and risk control teams throughout the model approval lifecycle.
• Support day-to-day analytics needs and participate in the continuous improvement of the platform.

Qualifications:

• Advanced degree (MSc/PhD) in a quantitative discipline such as Mathematics, Physics, Computer Science, Financial Engineering, or related quantitative field.
• Experience in a quantitative analytics or quantitative development role within a financial institution or a relevant industry.
• Strong experience in pricing and modelling derivatives, preferably in commodities, but FX, equities, or other complex products also considered.
• Solid knowledge of volatility modelling techniques and derivative pricing theory.
• Proficiency in C++ and Python for numerical computing and model development.
• Knowledge of working within a structured software development environment.  Use of source code control systems, continuous integration environments, testing, release processes, etc.
• Excellent problem-solving skills, attention to detail, and strong communication abilities.
• Experience with model documentation and familiarity with model validation processes is a strong plus.

Preferred Skills:

• Exposure to commodities markets (including, but not limited to energy, metals, ags, gas, power, index).
• Familiarity with Monte Carlo methods, PDE solvers, and volatility calibration techniques.

Minimum Education Requirement: Master’s degree in related field or equivalent work experience

Shift:

Hours Per Week: