Credit Risk Quantitative Model Analyst Sr

Job Responsibilities

• Develop and apply mathematical or statistical theory and methods to collect, organize, interpret, and summarize numerical data sets from multiple sources to develop credit risk rating models or other credit risk-related initiatives.
• Sourcing, cleaning, and transforming data; researching applicable methods; training and testing a variety of specifications.
• Documenting all facets of the development process; implementation of models and related logic in production systems.
• Auditing and assessing outputs across different levels of inputs (sensitivity analysis and scenario analysis).
• Back-testing and ongoing performance monitoring.
• Communicating aspects of the model and its application to non-technical stakeholders.

Job Requirements

• Education level required: Undergraduate Degree (4 years or equivalent)
• Minimum experience required: 6+ Years of model development, model performance monitoring or validation experience, particularly in credit risk.
• Experience with at least one of the following software packages: R, SAS, SQL, Python.

Preferred Qualifications

• Education level preferred: Master's Degree (or Postgraduate equivalent)
• Master’s degree in Statistics, Econometrics, Mathematics or related quantitative field.
• Experience with commercial dual risk rating frameworks, especially in PD/LGD/EAD modeling approaches.
• Experience developing credit risk models and programming user interfaces.
• Experience with nCino implementation of risk rating models and financial spreading process.
• Working knowledge of Generally Accepted Accounting Principles (GAAP), Basel III, Dodd-Frank Act Stress Testing, CCAR, and bank accounting/regulatory reporting requirements.
• Ability to use advanced statistical and mathematical software to perform descriptive, predictive, and prescriptive analysis leveraging a variety of statistical techniques (such as segmentation, logistic regression, sensitivity analysis, and machine learning).