Quantitative Finance Analyst
About The Position
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. Global Risk Analytics (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. In addition to model development, GRA conducts model implementation, data management, model execution and analysis, forecast administration, and model performance monitoring. The team drives innovation, process improvement and automation across all of these activities. 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). The right candidate will be required to contribute across the full spectrum of model development lifecycle tasks and will be important to the successful delivery of models in this space. In addition the right candidate will be needed to contribute more broadly to the regulatory driven suite of alternative and champion models developed by the team.
Requirements
- Highly numerical degree (Masters required; PhD level desirable) in Statistics, Financial Mathematics, Applied Mathematics, Economics, Physics or Engineering
- Some experience in developing, documenting & maintaining risk and/or capital models and handling large datasets
- Technical skills: Statistics, Probability Theory, Econometrics, Financial Mathematics
- Strong programming skills; SQL, Python, VBA, Latex
- 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
Nice To Haves
- Experiences in the areas of financial risk modelling, loss forecasting etc. preferred
- Knowledge of regulatory guidelines including CCAR, DFAST, CECL, ICAAP.
- Strong stakeholder engagement skills with an ability to work with colleagues in other functions (business, risk and model validation)
- Organized, practical and execution focused with some project management experience
- Self-motivated and intellectually curious about both the role, supporting technologies and the wider bank
- Experience with LaTeX
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
- Required to pro-actively seek out effective statistical estimation techniques required to model risk across the businesses supported
- Pro-actively work with stakeholders across the business(es) to collect requirements and then develop and build modelling solutions to meet them
- Implement the model using well written and well governed python code
- Produce clear and coherent technical documentation for internal and regulatory purposes
- Promote the adoption of, and personally meet, GRA best practices for model development, implementation and monitoring
- Critical to the role is to be able to think outside the box of current industry standards to develop innovative approaches to modelling problems
Benefits
- access to paid time off
- resources and support to our employees
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
