Credit Risk Modeler

Credit Risk Modeler / Quantitative Analyst

We are seeking a highly skilled and motivated individual with a strong understanding of predictive modeling techniques and their practical application. This role requires expertise in credit lifecycle statistics and machine learning techniques , coupled with robust programming and communication skills.

Required Qualifications :

• Master's degree in Mathematics, Statistics, Economics, Engineering, or a related quantitative discipline, or a demonstrated track record of performance proving equivalent ability.
• Very good understanding of Predictive modeling techniques and their application.
• Knowledge of Credit life cycle Statistics and machine learning techniques.
• Experience conducting and applying statistical methodologies including linear regression, logistic regression, ANOVA / ANCOVA, CHAID / CART, and cluster analysis.
• Good understanding of Probability of Default (PD), LGD, and EAD modeling techniques.
• Demonstrated knowledge in credit and / or market risk measurement and management.
• Excellent problem-solving, communication, and data presentation skills.
• Strong written and oral presentation / communication skills – must have the ability to convey complex information simply and clearly.
• Proficiency in SAS, SQL, GCP, R, and PYTHON.
• Fluency with Excel, PowerPoint, and Word.

Key Responsibilities :

Skills Required

Market Risk, Logistic Regression, Anova, Sas, Analytical, Predictive Modeling, Python