- This position within Global Consumer Banking will develop CCAR/DFAST stress loss models for secured portfolios (e.g., Home Equity, Mortgage etc.). The responsibility includes but not limited to the following activities:
- Obtain and conduct QA/QC on all data required for stress loss model development
- Develop segment and/or account level stress loss models
- Perform all required tests (e.g. sensitivity and back-testing)
- Validate/recalibrate all models annually to incorporate the latest data. Redevelop as needed.
- Deliver comprehensive model documentation
- Work closely with cross-functional teams, including country/region's business stakeholders, model validation and governance teams, and model implementation team
- Prepare responses/presentations for regulatory agencies on all regulatory models built
- Advanced Degree (Masters required or PhD preferred) in Statistics, Applied Mathematics, Operations Research, Statistics, Economics, Quantitative Finance etc. MBA s should apply only if they are interested in career in specialized quantitative risk management discipline.
- Role involves strong programming (SAS, R, Matlab etc) and quantitative analytics (regression, time series, decision tree, linear/nonlinear optimization etc) skill.
- Experience in performing quantitative analysis, statistical modeling, loss forecasting, loan loss reserve modeling, and particularly econometric modeling of consumer credit risk stress losses
- Experience in model development or (risk/marketing)- credit scorecard development, Basel modeling, stress loss preferred or credit policy analytics
- Experience in end-to-end modeling process (data collection, data integrity QA/QC/reconcilements, pre-processing, segmentation, variable transformation, variable selection, econometric model estimation, sensitivity testing, back testing, out-of-time testing, model documentation, & model production implementation)
- Good communication skill to communicate technical information verbally and in writing to both technical and non-technical audiences
- Expected to work with moderate supervision and guidance
- Work as an individual contributor