Credit Risk Quantitative Analyst
Seacoast Bank
Date: 7 hours ago
City: Saint Petersburg, FL
Contract type: Full time

JOB SUMMARY:
The Quantitative Credit Risk Analyst will play a key role in developing and implementing statistical and quantitative methodologies to support credit and non-credit loss forecasting, as well as economic and capital calculations. This role requires leveraging strong analytical and problem-solving skills to assess portfolio risk, optimize pricing strategies, and inform customer origination strategies across diverse portfolios, including consumer, residential, and commercial lending. The ideal candidate will combine technical expertise with business acumen to deliver actionable insights that drive sound risk management and strategic decision-making.
ESSENTIAL DUTIES AND RESPONSIBILITIES:
The Quantitative Credit Risk Analyst will play a key role in developing and implementing statistical and quantitative methodologies to support credit and non-credit loss forecasting, as well as economic and capital calculations. This role requires leveraging strong analytical and problem-solving skills to assess portfolio risk, optimize pricing strategies, and inform customer origination strategies across diverse portfolios, including consumer, residential, and commercial lending. The ideal candidate will combine technical expertise with business acumen to deliver actionable insights that drive sound risk management and strategic decision-making.
ESSENTIAL DUTIES AND RESPONSIBILITIES:
- Develop and validate credit risk models, including Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD) for lending portfolios.
- Develop model monitoring plan, monitor statistical model performance, including back testing and benchmark the model performance.\Support stress testing, scenario analysis, and model risk governance processes.
- Collaborate with cross-functional teams to ensure alignment of modeling approaches with CECL requirements and capital planning frameworks.
- Prepare comprehensive model documentation in compliance with internal and regulatory standards.
- Communicate technical subject matter to individuals from various backgrounds.
- Advanced degree in a quantitative discipline (e.g., Statistics, Mathematics, Economics, or related field).
- 3+ years of experience in credit risk modeling within banking or financial services.
- Knowledge of multivariate statistics, machine learning, and predictive modelling.
- Strong SAS programming skills, including SAS macro-language.
- Proficiency in Python, R, SQL, GIT, and familiarity with model validation frameworks.
- Self-motivated to proactively learn and solve complex business problems.
- Strong ability to explain complex subject matter to a non-technical audience.
- Strong attention to detail.
- Excellent communication, interpersonal, organization, and time-management skills.
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