Quant Developer - Quantitative Strategies & Data Group

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!

We are looking for a highly skilled and innovative Quant Developer / Strategist to join the Quantitative Strategies & Data Group within Global Markets. The team develops Python-based solutions on the Bank's strategic platform, Quartz, delivering strategic and regulatory programmes, including FRTB IMA, VaR, Strategic Risk and PnL, etc.. The role offers exposure across all asset classes (Rates / Commodity / Credit / FX / Equity) and involves close collaboration with Front Office Technology, Risk, and Quant teams. This is a hands-on role combining quantitative modelling, data analysis and engineering.

Key Responsibilities:

• Develop and enhance market models (e.g. VaR) to ensure accurate measurement of risk exposures across trading books, in line with regulatory and internal governance requirements
• Support the implementation of robust risk data testing frameworks to assess the appropriateness, completeness and reasonableness of risk scenarios, VaR, expected shortfall and stress test calculations. This includes testing scenario design, implementation, results consolidation, and analyses of calculations to understand key drivers
• Investigate data issues and model anomalies, expanding and debugging the existing risk and PnL calculation code, and improving performance and maintainability
• Partner with Tech, Quants and Risk partners to ensure that the solutions are scalable and aligned with the programmes' needs
• Drive continuous improvement through critical review of model development and validation outcomes, and constructive challenge and feedback on technical documentation

• Masters/PhD level in a quantitative subject (Mathematics, Statistics, Physics, Engineering, Computer Science or other analytical background)
• Proficient in Python, SQL, C++ and other
• Excellent analytical and problem-solving skills
• Strong communication skills
• Risk knowledge is desirable but not strictly necessary, provided there is a willingness to learn
• We welcome applications from junior candidates with at least 2 years of financial markets experience, as well as from more experienced professionals