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. 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 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.

Responsibilities:

• 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

• 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 Solutions Engineering - 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.

• Software development: implement, maintain, improve and integrate quantitative solutions on strategic GRA platforms. Development takes place almost entirely in Python, with some C++ for high performance components.
• Maintain code quality through best practices, unit testing and code quality automation.
• Understand the whole product, its modules, and the interrelationship between them, while being an expert in the assigned component or module.
• Possess advanced domain knowledge and show great customer focus. Leverage skills in methodologies and build, release, and deployment processes.
• Partner in defining, adopting, and executing GRA's technical strategy.
• Identify and apply new software development techniques to support enhanced granularity of risk management capabilities. Employ elevated intellectual curiosity and an acute sense of innovation.
• Elevated intellectual curiosity with acute sense of innovation to identify and apply new statistical and econometric techniques to support enhanced granularity of risk management capabilities
• Articulating the overall holistic picture of model performance, with clear conclusions regarding accuracy and remediation areas as required

• Strong Python software development skills
• Familiar with software design principles: separation of concerns, single responsibility, DRY, etc.
• Understanding of algorithms and data structures
• Experience with Linux operating system and command line tools
• Experience with version control systems, i.e., Git
• Knowledge of SQL
• Strong communication skills and ability to effectively communicate quantitative topics to technical and non-technical audiences
• Strong team player able to seamlessly transition between contributing individually and collaborating on team projects; Understands that individual actions may require input from manager or peers; Knows when to include others
• Experience implementing models into various production environments
• Demonstrated leadership skills; Ability to exert broad influence among peers
• Strategic thinker that can understand complex business challenges and potential solutions
• Sees the broader picture and is able to identify new methods for doing things
• Ability to work in a large, complex organization, and influence various stakeholders and partners
• Ability to work in a highly controlled and audited environment
• Exceptional programming skills in high performance python
• Exceptional Terabyte-scale Spark programming and optimization

• GRA Core Platform (GCP) experience
• Familiar with systems architecture concepts: service based, layered, microservices, scalability patterns
• Experience with engineering complex, multifaceted processes that span across teams; Able to document process steps, inputs, outputs, requirements, identify gaps and improve workflow
• Experience creating, optimizing, and debugging software solutions deployed into distributed computing environments (experience with Spark is a plus)
• Familiar with use of vectorization and data locality concepts to optimize software efficiency
• Experience with high performance Python libraries, i.e., Numpy, Numba, Cython
• Experience with LaTeX
• Familiarity with SDLC tools: unit testing libraries, Jira, Jenkins
• Consumer Financial Product Industry experience

• 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