Quantitative Finance Analyst

Bank of America • Charlotte, NC

7d • Onsite

About The Position

At Bank of America, the Quantitative Finance Analyst conducts quantitative analytics and modeling projects, supporting model development and enhancements to existing Wholesale and Consumer loss-forecasting models. The role contributes across the full model development lifecycle and to regulatory-driven alternative and champion models, with potential to support other areas including Global Financial Crimes, Finance, Markets, Capital, and Physical Climate Risk.

The analyst seeks effective statistical estimation techniques, works with business stakeholders to gather requirements and build modeling solutions, implements models in governed Python code, and produces technical documentation for internal and regulatory purposes. The position also supports model implementation, data management, model execution and analysis, forecast administration, model performance monitoring, and process improvement. The role calls for innovative approaches to modeling problems and adherence to Global Risk Analytics best practices.

Global Risk Analytics is part of Global Risk Management and develops models and analytical tools for risk and capital measurement, management, and reporting across Bank of America. The bank describes its work environment as committed to in-office collaboration, engagement, and career development, with role-specific flexibility based on responsibilities and business needs.

Requirements

• Master’s degree in a related field or equivalent work experience; a highly numerical degree is required, with Statistics, Financial Mathematics, Applied Mathematics, Economics, Physics, or Engineering given as examples.
• Some experience developing, documenting, and maintaining risk and/or capital models and handling large datasets.
• Knowledge of statistics, probability theory, econometrics, and financial mathematics.
• Strong programming skills in SQL, Python, VBA, and LaTeX.
• Strong technical writing and clear verbal communication skills.
• Ability to work under pressure and deliver to tight deadlines.
• Ability to work independently, multitask, and prioritize work effectively.
• Curiosity and willingness to develop and work on new modeling approaches.
• Broad knowledge of financial markets and products.
• Ability to think beyond current industry standards to develop innovative approaches to modeling problems.

Nice To Haves

• PhD-level education.
• Experience in financial risk modeling and loss forecasting.
• Knowledge of regulatory guidelines including CCAR, DFAST, CECL, and ICAAP.
• Strong stakeholder engagement skills and ability to work with colleagues in business, risk, and model validation.
• Organization, practicality, execution focus, and some project management experience.
• Self-motivation and intellectual curiosity about the role, supporting technologies, and the wider bank.

Responsibilities

• Conduct quantitative analytics and modeling projects for specific business units or risk types.
• Perform end-to-end market risk stress testing, including scenario design and implementation, results consolidation, internal and external reporting, and analysis of scenario drivers.
• Support planning and prioritization of quantitative work in line with the bank’s strategy.
• Review relevant model development and validation approval decisions, provide critical feedback on technical documentation, and challenge model development and validation work to identify improvements and potential risks.
• Support model development and model risk management in assigned focus areas in accordance with business requirements and enterprise risk appetite.
• Provide methodological, analytical, and technical guidance to challenge and influence development and validation project approaches.
• Communicate submission and validation outcomes to model stakeholders and senior management.
• Perform statistical analysis on large datasets and interpret results using qualitative and quantitative approaches.
• Seek effective statistical estimation techniques for modeling risk across supported businesses.
• Work with business stakeholders to gather requirements and build modeling solutions.
• Implement models using well-written, well-governed Python code.
• Produce clear technical documentation for internal and regulatory purposes.
• Promote and follow Global Risk Analytics best practices for model development, implementation, and monitoring.
• Contribute to enhancements of existing Wholesale and Consumer loss-forecasting models and development of new models.
• Work with Technology staff on the design of systems to run developed models.

Benefits

• The company describes its benefits as affordable, competitive, and flexible, and says it supports teammates’ physical, emotional, and financial wellness; specific benefit offerings are not listed.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level