Description

You will develop and maintain credit risk models and analytical frameworks to evaluate loan portfolio performance.

Responsibilities

• Build credit risk models to compute expected credit loss (ECL), develop early warning system (EWS) methodologies, and conduct stress testing.
• Design and sustain scorecards and dashboards to provide timely insights into portfolio risk performance.
• Aggregate and consolidate data from multiple internal and external sources for use in risk dashboards and machine learning models.
• Execute qualitative and quantitative evaluations of performance metrics and deliver findings to internal stakeholders.
• Improve existing risk monitoring reports and handle ad-hoc data requests across underwriting and risk domains.

Required Skills

• 3+ years of experience in data science or risk analytics.
• Proficiency in Python or R for statistical analysis and deploying machine learning algorithms.
• Strong experience with SQL for data aggregation and manipulation.
• Experience with Power-BI for dashboard development.
• Practical application of regression, decision trees, and cluster analysis.
• Expertise in financial modeling, logistic regression, and scorecard development.
• Ability to work with both conventional and non-traditional data sources.
• Background in risk analysis and statistical modeling.
• Any Graduate degree in Business Administration, Statistics, or a related field.

Key Skills

Education

Any Graduate