Bank of America is a global financial institution operating across banking, finance, and fintech. Its services include personal banking, small-business support, wealth management, investment services, and access to capital markets for individuals, businesses, and institutions. The company also focuses on responsible growth through sustainable finance, diversity initiatives, and community development programs.
Quantitative Finance Analyst, Credit Risk Models — Bank of America
Develop and oversee wholesale credit risk models within Bank of America’s Global Risk Analytics function. The role covers model development, validation, monitoring, and communication to support credit risk management.
Description
- Develop wholesale credit risk models for loss forecasting, commercial and behavioral scoring, and regulatory capital.
- Analyze wholesale credit performance and financial data in depth.
- Write white papers documenting developed models.
- Work with internal model risk management, resolve concerns, and address model findings.
- Support model implementation follow-up, ongoing monitoring, reviews, and stakeholder engagement.
- Independently carry out quantitative analyses and complex modeling projects.
- Lead the creation of new models, analytical processes, and system approaches.
- Document all work and activities.
- Partner with technology teams to build systems that run developed models.
- Assess bank model results through benchmarking and sensitivity analysis.
- Explain model performance, accuracy, and areas requiring remediation.
- Present model results to risk management, model development and risk teams, senior management, and regulators.
Requirements
- Master’s degree in mathematics, economics, statistics, engineering, finance, computer science, or a related field, or equivalent professional experience.
- At least five years of professional experience developing credit risk models.
- Strong programming ability in languages such as R, Python, SAS, or SQL.
- Strong analytical and problem-solving capabilities.
- Experience using and developing cross-sectional models.
- Experience implementing models in production environments.
- Ability to draw recommendations and conclusions from data.
- Ability to present findings and conclusions to senior leaders.
- Demonstrated leadership and ability to influence others.
- Ability to work in a large, complex organization and influence stakeholders.
- Strong communication skills with technical and non-technical audiences.
- Ability to work in a highly controlled, audited environment.
- Effective prioritization, time management, and project management.
- Experience with complex data architectures, data science tools and libraries, data warehouses, and machine learning.
- Ability to extract, analyze, and combine data from disparate systems.
- Experience developing and maintaining complex databases and datasets.
- Experience applying data mining and advanced analytical methods.
- Experience managing large datasets with tools such as Hadoop.
- Experience designing, developing, and applying scalable machine learning and artificial intelligence solutions.
- Experience with data analytics and visualization tools such as Alteryx, Tableau, and MicroStrategy.
- Experience using LaTeX.
- Experience building data architectures suited to retrieving, analyzing, storing, cleansing, and transforming large datasets.
- Experience managing project tasks and timelines across teams.
- Experience engineering complex processes that span multiple teams.
Benefits
- Eligible for an annual discretionary incentive plan.
- Industry-leading benefits.
- Paid time off.
- Employee resources and support.
- In-office culture with flexibility specific to the role.
- Opportunities to learn, grow, and make an impact.