Quantitative Finance Analyst

About the Role

At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We are intentional about fostering an inclusive workplace where every teammate has the opportunity to succeed, build a career and contribute to our shared success. Bank of America is committed to an in-office culture that supports collaboration, engagement, and career development. At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact.

About the Team

Global Risk Analytics (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. The AMG Team is responsible for developing and managing models across multiple domains, including Wholesale, Consumer and Global Financial Crimes. The team has a requirement for a highly-motivated Quantitative Finance Analyst to join us to support enhancements to existing Wholesale and Consumer loss forecasting models as well as developing new models. There is always the potential for further growth supporting one of the numerous other areas we support (Global Financial Crimes, Finance, Markets, Capital, Physical Climate Risk).

Key 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
• Contributes across the full spectrum of model development lifecycle tasks
• Contributes to the regulatory driven suite of alternative and champion models developed by the team
• Pro-actively seeks out effective statistical estimation techniques required to model risk across the businesses supported
• Pro-actively works with stakeholders across the business(es) to collect requirements and then develops and builds modelling solutions to meet them
• Implements the model using well written and well governed python code
• Produces clear and coherent technical documentation for internal and regulatory purposes
• Promotes the adoption of, and personally meets, GRA best practices for model development, implementation and monitoring
• Thinks outside the box of current industry standards to develop innovative approaches to modelling problems

Requirements & Tech Stack

• SQL
• Python
• VBA
• Latex
• Experience in developing, documenting & maintaining risk and/or capital models and handling large datasets
• Strong programming skills
• Strong technical writing and clear verbal communication skills
• Experience of, and ability to work under pressure and deliver to tight deadlines
• Ability to work independently, multitask and properly prioritize work
• Curiosity and willingness to develop and work on new ways of modelling

Qualifications

• Highly numerical degree (Masters required; PhD level desirable) in Statistics, Financial Mathematics, Applied Mathematics, Economics, Physics or Engineering
• Statistics
• Probability Theory
• Econometrics
• Financial Mathematics
• Experience in the areas of financial risk modelling, loss forecasting etc. (preferred)
• Knowledge of regulatory guidelines including CCAR, DFAST, CECL, ICAAP (preferred)
• Strong stakeholder engagement skills with an ability to work with colleagues in other functions (business, risk and model validation) (preferred)
• Organized, practical and execution focused with some project management experience (preferred)
• Self-motivated and intellectually curious about both the role, supporting technologies and the wider bank (preferred)
• Experience with LaTeX

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