Are you looking for an exciting opportunity to join a dynamic and growing team in a fast paced and challenging area? This is a unique opportunity for you to work in our team to partner with the Business to provide a comprehensive view.
 

As a Portfolio Risk - Cards CCAR Model Development Associate within the Portfolio Risk Modeling team, you will have the opportunity to support and develop regulatory models, execute and prepare model surveillance, and provide insights for various regulatory requirements. You will use your expertise in performance assessment methods and metrics for various types of risk models used in portfolio Risk, regulatory modeling, and forecasting methods. You will be responsible for the development of stress test models as part of the annual CCAR/CECL exercise. This role will allow you to utilize your experience with econometric/statistical modeling, data manipulation, query efficiency techniques, reporting, and automation. We value intellectual curiosity and a passion for promoting solutions across organizational boundaries.

 

Job Responsibilities:

Design, develop, test, and validate statistical models for ‘Cards’ Unsecured Lending portfolio risk forecast and model performance monitoring Utilizing graduate-level research and analytical skills to perform data extraction, sampling, and statistical analyses using logistic regression, multinomial regression, multivariate analysis, discriminant analysis, time series analysis, panel data analysis, Survival Hazard Rate Models etc. Efficiently design and produce programs to streamline and create repeatable procedures for model development, validation, and reporting Process, cleanse, and verify the integrity of data used for analysis Perform deep dive analysis to address ad hoc inquiries

Required qualifications, capabilities, and skills

MS, Engineering or PhD degree in a quantitative discipline Minimum 6+ years of hands-on work and research experience of advanced analytical skills in the areas of statistical modeling and data mining Proficiency in advanced analytical languages such as SAS, R, Python, PySpark Experience utilizing SQL in a relational database environment such as DB2, Oracle, or Teradata Ability to deliver high-quality results under tight deadlines Strong multi-tasking skills with demonstrated ability to manage expectations and deliver results

Preferred qualifications, capabilities, and skills

Knowledge of regulatory modeling (IFRS9/CECL/CCAR preferred)