Quantitative Finance Analyst

Job Description:

At Bank of America, models are used for a broad range of activities, including but not limited to valuation, risk management, capital and liquidity planning, stress testing, underwriting and other strategic or day-to-day decision-making purposes. Bank of America recognizes the risk and uncertainty associated with the use of its models and the need to effectively manage this risk both at an individual level and in the aggregate.

The Model Risk Management (MRM) Team provides oversight for model risk across Bank of America's model inventory.  The MRM Team independently validates and challenges newly-developed and existing models; is responsible for model risk assessments, limits and monitoring; communicates issues identified through validations to relevant businesses and governance and control functions; and escalates model use breaches and remediation plans to relevant governance committees.

The successful candidate will be joining the MRM Team covering models used in e-Trading as well as pricing models for Equities and Commodities derivatives. The Quantitative Finance Analyst will be responsible for overseeing model risk management activities pertaining primarily to algorithmic trading and machine learning models, but will also have the opportunity to work with pricing models.

• PhD or Master's degree in Mathematics, Engineering, Physics, Computer Science / Machine Learning, or related field
• Strong prior experience of model risk management or quantitative modelling at a financial institution
• Strong written and verbal communication skills including ability to communicate clearly, effectively, and work well with people at all levels
• Strong knowledge of data science, electronic trading and statistical theories
• Deep understanding of the modelling process, model performance measures, and model risk.
• Ability to manage multiple projects, follow up with issues and summarize discussions
• Familiar with machine learning platforms/software (e.g., Python / sklearn, XGBoost, and R), algorithms, and techniques; and proficient in Python.

Job Band:

Shift: 

Hours Per Week:

Weekly Schedule:

Referral Bonus Amount: