Senior Quantitative Fin Analyst - Non-Registered

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!
 

Job Summary:

The BSM IFAR team works with the broader Treasury and LOB Finance team to support LOB and Finance partners through analytics and reporting to communicate the story of the Company’s financial results to stakeholders. This team is responsible for coordinating, consolidating, analyzing, and reporting balance sheet forecast results under various scenarios including baseline and stress. This role also plays a critical role in forecasting net interest income (NII), Treasury non-interest income, and to explain the driver of our forecasts such as change in the market yields, the LOB business strategy by line of business, legal entity, and product.

The successful candidate will apply advanced quantitative techniques to solve complex problems in finance, risk management, and asset liability management. This role will involve developing and implementing statistical models, analyzing large datasets, and providing insights to support key decision-making activities.

Key Responsibilities:

• Completing research and application of quantitative techniques in finance, applying mathematics, and statistics to solve forecasting, risk measurement and management problems.
• Applying all aspects of quantitative model development and management for statistical/quantitative analysis, development of statistical/quantitative models, creating technical documentation consistent with enterprise model risk standards
• Partnering with the development/quants team on implementation and maintenance of models/systems
• Analyzing extensive quantitative methods for effective asset liability management
• Supporting the application of behavioral and forecasting models for all loans and deposit products on the bank’s balance sheet along with pricing and valuation tools for the bank’s traded discretionary portfolio
• Supporting key decision-making activities including:
  • Market Execution for discretionary portfolio and global funding
  • Interest Rate Risk Management
  • Balance Sheet Management
  • Liquidity Management
  • Associated CCAR processes
• Programming with Statistical Programming Software such as R, SAS, Python
• Developing and analyzing statistical models using statistical and econometric methods such as linear regression, time series, logistic regression, and panel methods
• Generating statistical analysis to support stress testing, asset liability management
• Using SQL for financial data processing and analysis
• Applying quantitative methods to fixed income valuation, financial engineering, computational optimization for risk management

Requirements:

• Bachelor's degree in a quantitative field (e.g. mathematics, statistics, economics, computer science, or engineering)
• Minimum 5 years of experience in quantitative finance or a related field
• Strong programming skills in languages such as R, SAS, Python, and SQL
• Experience with statistical modeling and data analysis
• Strong understanding of financial markets, instruments, and risk management concepts
• Excellent communication and collaboration skills

Desired Qualifications:

• Familiarity with Treasury / balance sheet management topics.
• Familiarity with machine learning and artificial intelligence techniques
• Knowledge of financial regulations and risk management frameworks (e.g. CCAR, Basel III)
• Experience with model risk development, management, and validation
• Strong understanding of computational optimization techniques and their application to risk management

Skills:

• Critical Thinking
• Quantitative Development
• Risk Analytics
• Risk Modeling
• Technical Documentation
• Adaptability
<