Provides analytical and technical support for the development, refinement, and ongoing monitoring of credit risk models used to meet regulatory requirements and support the Bank’s strategic risk management objectives.
This includes models for loss forecasting, default probability estimation, and other credit‑sensitive behaviors across lending portfolios.
Performs data preparation, exploratory data analysis, and model estimation under the guidance of senior modelers, leveraging strong quantitative skills and proficiency in Python, SQL, and statistical methods.
Collaborates with Credit Risk Management, Model Risk Management, and business line partners to ensure model methodologies, assumptions, and outputs align with regulatory expectations and the Bank’s broader credit risk framework.
Communicates analytical results through clear narratives, visualizations, and documentation that support model development, validation activities, and ongoing performance monitoring.

Bachelor’s degree and a minimum of one year of proven quantitative behavioral modeling experience, or a combined minimum of five years of higher education and/or work experience, including at least one year of quantitative modeling experience.
Minimum of one year of on‑the‑job experience using statistical software packages such as SAS, Python, or R.
Strong Python skills required.
Model development experience required, including familiarity with logistic and linear regression techniques.
Minimum of one year of experience working in a data management environment such as SQL Server Management Studio.
Minimum of one year of experience managing and analyzing large datasets, with the ability to communicate results clearly using written, verbal, and visual formats.

Credit Model Development Quantitative Analyst II – Small Business and Home Secured

Key skills