Quantitative Finance Analyst - Consumer Model Development & Operations (CMDO) Team

Bank of America

Bank of America

IT, Accounting & Finance, Operations
Charlotte, NC, USA · Chicago, IL, USA · Atlanta, GA, USA · United States · Remote
Posted on Thursday, June 6, 2024

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:
This job is responsible for conducting quantitative analytics and modeling projects for specific business units or risk types. Key responsibilities include developing new models, analytic processes, or systems approaches, creating technical documentation for related activities, and working with Technology staff in the design of systems to run models developed. Job expectations include having a broad knowledge of financial markets and products.


  • Performs end-to-end market risk stress testing including scenario design, scenario implementation, results consolidation, internal and external reporting, and analyzes stress scenario results to better understand key drivers
  • Supports the planning related to setting quantitative work priorities in line with the bank’s overall strategy and prioritization
  • Identifies continuous improvements through reviews of approval decisions on relevant model development or model validation tasks, critical feedback on technical documentation, and effective challenges on model development/validation
  • Supports model development and model risk management in respective focus areas to support business requirements and the enterprise's risk appetite
  • Supports the methodological, analytical, and technical guidance to effectively challenge and influence the strategic direction and tactical approaches of development/validation projects and identify areas of potential risk
  • Works closely with model stakeholders and senior management with regard to communication of submission and validation outcomes
  • Performs statistical analysis on large datasets and interprets results using both qualitative and quantitative approaches


  • Critical Thinking
  • Quantitative Development
  • Risk Analytics
  • Risk Modeling
  • Technical Documentation
  • Adaptability
  • Collaboration
  • Problem Solving
  • Risk Management
  • Test Engineering
  • Data Modeling
  • Data and Trend Analysis
  • Process Performance Measurement
  • Research
  • Written Communications

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

Consumer Model Development & Operations – Quantitative Financial Analyst (B5)

Job Description
Bank of America Merrill Lynch has an opportunity for a Quantitative Financial Analyst within our Global Risk Analytics (GRA) function. GRA is a sub-line of business within Global Risk Management (GRM). GRA is responsible for developing a consistent and coherent set of models and analytical tools for effective risk and capital measurement, management and reporting across Bank of America. GRA partners with the Lines of Business and Enterprise functions to ensure that its models and analytics address both internal and regulatory requirements, such as quarterly Enterprise Stress Testing (EST), the annual Comprehensive Capital Analysis and Review (CCAR), and the Current Expected Credit Losses (CECL) accounting standard. GRA models follow an iterative and ongoing development life cycle, as the bank responds to the changing nature of portfolios, economic conditions and emerging risks. In addition to model development, GRA conducts model implementation, data management, model execution and analysis, forecast administration, and model performance monitoring. GRA drives innovation, process improvement and automation across all of these activities.

Overview of Consumer Model Development
The Consumer Model Development & Operations (CMDO) team is part of Global Risk Analytics. It provides quantitative solutions to enable effective risk and capital management across the Retail and Global Wealth & Investments Management (GWIM) lines of business.

The team places strong emphasis on delivering world class quantitative solutions for Front Line Unit (FLU) model owners and stakeholders through a disciplined and iterative development process. The team has responsibilities across a number of areas:

• Quantitative Modeling – Develop and maintain risk and capital Models and Model Systems across Retail and GWIM product lines. Models and Model Systems provide insight into many risk areas, including loan default, exposure at default (EAD), loss given default (LGD), delinquency, prepayment, balances, pricing, risk appetite, revenues and cash flows.
• Quantitative Development – Architect, implement, maintain, improve and integrate quantitative solutions on strategic GRA platforms. Outputs include GRA libraries that perform consumer risk model calculations, analytical tools, processes and documentation. Partner in defining, adopting, and executing GRA’s technical strategy.
• Risk and Capital Management Capabilities – Build best in class quantitative solutions that enable the Retail and GWIM lines of business to effectively manage risk and capital, through the application of the disciplined BAU development process that includes extensive interaction with the FLU model owners and stakeholders throughout the quantitative lifecycle.
• Infrastructure – Partner in driving forward the infrastructure to support the goals of GRA through code efficiencies, and expansion of quantitative capabilities to better leverage infrastructure and computational resources.
• Documentation – Deliver concise, quantitative documentation to inform stakeholders, meet policy requirements, and enable successful engagement in regulatory exams (e.g., CCAR, CECL) via automated, modularized, and standardized documentation and presentations.

Role Responsibilities

  • Apply quantitative methods to develop new granular capabilities that meet risk management, line of business, and regulatory requirements.
  • Identify and apply new statistical and econometric techniques to support enhanced granularity of risk management capabilities.
  • Perform in-depth analysis on the risk model results using various quantitative tools such as back testing, benchmarking, and sensitivity analysis.
  • Analyze and assess large, complex financial dataset with programming tools such as Python, SAS, SQL and R.
  • Develop and analyze statistical models such as linear regression, auto regression, or logistic regression to assess model diagnostic and model performance.
  • Generate statistical analysis to support stress testing, credit risk management, regulatory examinations.
  • Create model documentation describing model development and testing to enable independent model validation. Conduct quantitative analysis on inputs and outputs for econometric models used in stress-testing.

Required Education, Skills, and Experience
Successful candidates will have a Masters or PhD in Math, Economics, Statistics, or similar discipline, and a minimum 2 years relevant experience in statistics, data science, econometrics, and other quantitative analysis.

Successful candidates will possess the following skills:
• First-hand experience in data analysis, statistical model estimation, implementation, and testing
• Strong programming skills in Python, SQL, Pandas and NumPy
• Quantitative documentation experience with LaTeX
• Strong analytical and problem-solving skills
• Effectively presents quantitative analysis to stakeholders

Desired Skills and Experience
The ideal candidate will possess the following skills and experience:

• Experience with HDFS, HIVE, and Spark
• Ability to apply CI/CD tools (e.g,, Git, JIRA, Confluence, Pytest, Jenkins, and SonarQube) in model development process
• In-depth business knowledge of Consumer and Wealth Management products
• Experience with CCAR and CECL


1st shift (United States of America)

Hours Per Week: