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
Overview of Global Risk Analytics (GRA) and Enterprise Independent Testing (EIT)
Bank of America Merrill Lynch has an opportunity for a Quantitative Financial Analyst within our Global Risk Analytics (GRA) function. Global Risk Analytics (GRA) and Enterprise Independent Testing (EIT) are sub-lines of business within Global Risk Management (GRM). Collectively, they are responsible for developing a consistent and coherent set of models, analytical tools, and tests for effective risk and capital measurement, management and reporting across Bank of America. GRA and EIT partner with the Lines of Business and Enterprise functions to ensure the capabilities it builds address both internal and regulatory requirements, and are responsive to the changing nature of portfolios, economic conditions, and emerging risks. In executing its activities, GRA and EIT drive innovation, process improvement and automation.
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 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.
The Quantitative Finance Analyst will interact with a wide variety of stakeholders including risk managers, model developers, operations, technology, finance, and capital.
The main responsibilities will involve:
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
Minimum Education Requirement: Master’s degree in related field or equivalent work experience
Required Qualifications: Successful candidates will have a minimum 5 years relevant experience and will possess the following skills:
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
Desired Qualifications: The ideal candidate will possess the following skills and experience:
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
Skills:
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
Shift:
1st shift (United States of America)Hours Per Week:
40