Model Developer - SQL/SAS - Global Consumer Banking

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 latest data. Redevelop as needed.

- Deliver comprehensive model documentation

- Work closely with cross functional teams, including country/regions business stakeholders, model validation and governance teams, and model implementation team

- Prepare responses/presentations for regulatory agencies on all regulatory models built

Education:

- 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.

Skillset

- 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