Lead Data Scientist- Credit Risk Modeling and Validation CCAR/CECL (Hybrid)

This position within Global Consumer Banking will develop CCAR/CECL/IFRS9 loss models for consumer and small business portfolios (e.g., credit cards, installment loans, ready credit etc.).

Responsibilities:

The responsibility includes but not limited to the following activities:

• Obtain and conduct QA/QC on all data required for CCAR/CECL/IFRS9 model development
• Develop segment and/or account level CCAR/CECL/IFRS9 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/region’s business stakeholders, model validation and governance teams, and model implementation team
• Prepare responses/presentations to regulatory agencies on all CCAR/CECL/IFRS9 models built

Qualifications:

• 6+ years for Bachelor’s or 2+ years for Master’s in performing quantitative analysis, statistical modeling, loss forecasting, loan loss reserve modeling, and/or particularly econometric modeling of consumer credit risk stress losses (e.g., CCAR/DFAST)
• Experience with dynamics of consumer products, with international experience a strong plus
• Active role in performing some analytical components of an econometric modeling-driven stress loss 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)
• Exposure to various CCAR/CECL/IFRS9 modeling approaches at the segment or account level preferred
• Exposure to project management of model development initiatives and prepare technical responses/presentations to internal model review functions and/or external regulators (e.g., FRB, OCC, FDIC) and internal audit functions
• Able to communicate technical information verbally and in writing to both technical and non-technical audiences
• Proficiency in SAS/SQL/Oracle/Unix/Microsoft Word, Excel and PowerPoint

Educations

• 6+ years for Bachelor’s or 2+ years for Master’s
• Advanced Degree ( Masters, PhD preferred) in Statistics, Mathematics, Operations Research, Economics, Financial Engineering, Mathematical Finance, Industrial Engineering, Data Science, and other highly quantitative disciplines

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