Credit Portfolio Senior Analyst

Duties

• Develop quantitative techniques to inform securities investing, equities investing, pricing, or valuation of financial instruments.
• Develop mathematical or statistical models for risk management, asset optimization, pricing, or relative value analysis.
• Perform credit review, approval, and portfolio monitoring.
• Develop credit techniques and procedural improvements.
• Identify areas for credit policy adjustments.
• Provide analytics at portfolio and segment levels for risk and profit optimization.
• Collaborate with Risk Management Information Systems (MIS) on Credit Risk Reporting and Portfolio Quality Review Reporting.
• Work with cross-functional teams in policy execution and management.
• Analyze credit and financial performance to recommend policy adjustments using statistical scoring, segmentation, regression, and simulation techniques.
• Analyze Cards portfolio performance at granular and product levels.
• Conduct data-driven root cause analysis using SAS and SQL to isolate key performance drivers.
• Develop credit tests and risk strategies using statistical and modeling techniques.
• Create tracking mechanisms for monitoring credit tests and expansions.
• Utilize SAS in a UNIX environment for risk, financial, and data analyses, including profiling, sampling, reconciliation, and quality testing.
• Evaluate and implement analytic tools to enhance reporting capabilities.
• Formulate objectives and develop analytical solutions using advanced segmentation techniques like PCA and CHAID.
• Write and integrate queries in SAS and SQL, ensuring reporting accuracy.
• Simplify data extraction processes to enhance datamarts.

Requirements

• Requires a Master’s degree, or foreign equivalent, in Statistics, Mathematics or related quantitative field and 1 year of experience as a Credit Risk Analyst or related position involving consumer credit risk management to mitigate risk in a global financial services institution.
• Alternatively, employer will accept a Bachelor’s degree in the specified fields and 3 years of experience in the above positions.
• 1 year of experience must include: Statistical analytics using SAS/SQL; Algorithm designing and analysis for behavior forecasting; SAS programming for data management; Regression analysis; Machine learning algorithm designing and implementation; Clustering analysis and risk segmentation; Simple and nonlinear regression models calculation; Model fit and assumption testing and variables adjustment; Experimental design including randomization, replication and control; Approximation of sampling distribution; Experimental data analysis for decision-making formulation and modeling; Credit risk management; Financial analysis; and Financial reporting.