Quantitative Finance 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. Responsible Growth is how we run our company and how we deliver for our clients, teammates, communities and shareholders every day.

One of the keys to driving Responsible Growth is being a great place to work for our teammates around the world. We’re devoted to being a diverse and inclusive workplace for everyone. We hire individuals with a broad range of backgrounds and experiences and invest heavily in our teammates and their families by offering competitive benefits to support their physical, emotional, and financial well-being.

Bank of America believes both in the importance of working together and offering flexibility to our employees. We use a multi-faceted approach for flexibility, depending on the various roles in our organization.

Working at Bank of America will give you a great career with opportunities to learn, grow and make an impact, along with the power to make a difference. Join us!

Job Description:
The role is part of the Global Banking team of Enterprise Model Risk Management. As part of second line of defense, the role has a unique opportunity to review a wide array of credit risk models used for underwriting, credit monitoring and regulatory capital decisions for the bank’s wholesale portfolio, which encompasses loans and leases made to commercial borrowers of various sizes and in various industries and straddles multiple LOBs from GCIB to GWIM. In managing model risk in this space, the candidate will engage with various groups of internal stakeholders and external regulators, develop a deep understanding of the business, and apply analytical skills/knowledge such as finance theories and statistical analysis to real-world problems faced by the bank. To be successful in this role, the candidate will not only possess intellectual curiosity to stay abreast of leading modeling practice, but also display a genuine interest in tracking emerging risks and assessing their impact on the bank’s portfolio.  

Responsibilities:

• Conduct thorough reviews and critical assessments of models, focusing on conceptual soundness, assumptions, data integrity, performance, implementation, and documentation.

• Develop and execute effective testing plans, benchmarks, and testing code to challenge models through empirical analyses and verify implementation accuracy.

• Engage in ongoing model review activities, including independent validation, ongoing monitoring report review, and addressing action items as necessary.

• Collaborate closely with Model Developers, Model Engineers, and Global Control Functions to prioritize and complete validation activities, ensuring alignment with organizational objectives.

• Provide support to senior management by delivering key findings and assisting in interactions with external regulators.

• Write technical reports for distribution and presentation to various stakeholders, including model developers, senior management, audit, and regulatory authorities.

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

Required Qualifications:

• Master's/Ph.D. in Economics, Data Science, Finance, Economics, Mathematics, Statistics, Engineering, Physics, Computer Science, or a related field.

• Minimum of 3 years of experience in statistics and econometrics (time series, regression modeling, etc.)

• Excellent coding ability in programming with Python, SAS or R.

• Experience working with large and complex data sets using Excel or SQL.

• Excellent communication and writing skills, with a keen attention to detail.

• Demonstrated ability to work effectively in a team environment with a strong work ethic.

Desired Qualifications:

• Experiences with commercial credit risk rating, capital estimation and loss forecasting

• Deep understanding and knowledge of model performance measures

• Extensive knowledge of banking regulations on credit risk, model risk and credit risk modeling methodologies.

Shift:

Hours Per Week: