Overview
This is a hybrid role with the expectation that time working will regularly take place inside and outside of a company office.
We are looking for candidates who live within a commutable drivable distance to our Raleigh, NC office.
We are seeking a highly skilled and motivated candidate to join our Modelling and Analytics team. This role is responsible for developing, maintaining, and enhancing credit risk models (PD/LGD/EAD/ECL) for various asset classes within the bank's loan portfolio. The candidate will apply these models for CECL reserve calculation and CCAR stress testing, ensuring regulatory compliance, accurate loan loss forecasting, and insightful analysis for senior leadership. This position requires close collaboration with data, credit, product management and risk teams to enhance model effectiveness and business decision-making.
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Responsibilities
Key responsibilities include:
- Develop and maintain loan loss forecasting models that align with CCAR and CECL regulatory requirements and support internal business needs.
- Prepare detailed model documentation, outlining model development, conceptual soundness, and outcomes, and submit it for validation and audit purposes.
- Utilize advanced analytical techniques to identify trends, analyze data and provide insights into potential performance impact.
- Prepare reports for senior leadership by summarizing model performance, key findings, and actionable insights to support decision-making.
Finally, the position offers the opportunity to be part of a team of modeling experts with graduate degrees in mathematics, finance, economics, and data science; and experiences from top-tiers market research firms, academic institutions, and management consulting companies.
Qualifications
Bachelor's Degree and 2 years of experience in financial, statistical, or quantitative analysis experience OR High School Diploma or GED and 6 years of experience in financial, statistical, or quantitative analysis experience.
Preferred Area of Experience:
- Previous experience in SQL project and financial modeling.
- Proficient in data analysis and visualization tools, including Python, R, SQL, and advanced Excel.
- Financial math, data science, economics, statistics.
- Master's/PhD degree in finance, economics, mathematics, statistics, or data science.