Quantitative Finance Analyst

Job Description:

GRA is a sub-line of business within Global Risk Management GRM 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), the Current Expected Credit Losses (CECL) accounting standard and more recently, Climate Risk forecasting.

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.

Overview of Wholesale Forecast Analytics team and role:

Forecast Administration and Analytics employees possess a broad set of skills necessary to evaluate financial risk, produce regulatory reporting and evaluate portfolio risk for emerging, systemic, concentration and idiosyncratic risks. They collaborate with business partners to identify risk mitigation strategies. They possess high levels of skill in portfolio analysis, econometrics, financial analysis and data visualization. The team welcomes a diversity of thoughts and experiences grounded in a core set of competencies with the ability to connect data points from across the enterprise. The team is also responsible for performing complex analysis and is engaged in the development of modeling that maximizes profits and asset growth and minimizes credit and operating losses and other risk exposures. Provides analytical support on various product strategies to ensure company goals are met. Coordinates the production of performance reports for Senior Management. Reviews and analyzes trends in current population distributions and recommends strategies. The  May participate in or develop complex program models to extract data and use databases to provide statistical and financial modelling.

Education and Experience requirements:

• Masters' Degree in Math, Statistics, Economics or similar discipline;  2+ years of non-internship experience

• Understanding of credit products

• Ability to work in a large, complex organization, and influence various stakeholders and partners

• Self-starter; Initiates work independently, before being asked

• 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

• Strong communication skills and ability to effectively communicate quantitative topics to technical and non-technical audiences

• Experience with engineering complex, multifaceted processes that span across teams; Able to document process steps, inputs, outputs, requirements, identify gaps and improve workflow

• Strong analytical and problem-solving skills

• Understanding of Credit Products Languages: Python, R, SQL; Database Tools: Hadoop, Teradata, Exadata (Oracle); Other: Tableau, Jira, Alteryx

Preferred skills:

• Languages: Python, R, SQL

• Database Tools: : Hadoop, Teradata, Exadata(Oracle)

• Other: Tableau, Jira, Alteryx

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