About the job
Job Id: 22481968
The Model/Anlys/Valid Mgr provides full leadership and supervisory responsibility. Provides operational/service leadership and direction to team(s). Applies in-depth disciplinary knowledge through provision of value-added perspectives or advisory services. May contribute to the development of new techniques, models and plans within area of expertise. Strong communication and diplomacy skills are required. Generally has responsibility for volume, quality, timeliness of end results and shared responsibility for planning and budgets. Work affects an entire area, which eventually affects the overall performance and effectiveness of the sub-function/job family.Full supervisory responsibility, ensuring motivation and development of team through professional leadership to include duties such as performance evaluation, compensation, hiring, disciplinary and terminations as well as direction of daily tasks and responsibilities.
- Obtain and conduct QA/QC on all data required for CCAR/CECL/Decision Scores model development
- Develop segment and/or account level CCAR/CECL/Decision Scores models. Developing Underwriting, Line management, Account management, Collection and Recovery models.
- Executing the above models in compliance with GCCFRP and in accordance with the Model Development Procedures within Risk
- Validate/recalibrate all models annually to incorporate latest data. Redevelop as needed.
- Perform all required tests (e.g. sensitivity and back-testing). Deliver comprehensive model documentation and perform implementation tests
- Work closely with cross functional teams, including business stakeholders, model validation and governance teams, and model implementation team
- Work closely with policy managers in establishing the swap set analysis and PnL optimization using the models.
- Create story boards, presentations and project plans for discussions with senior management
- Support the regulatory submissions for Citi on CCAR/CECL and work on adhoc requests from Business and Independent Risk
- Prepare responses/presentations to regulatory agencies on all CCAR models built
- Train and mentor junior modeler in developing innovative models in compliance with policies and procedures
- Advanced Degree (Masters required, PhD preferred) in Statistics, Applied Mathematics, Operations Research, Economics, MBA (Finance), or other highly quantitative discipline
- 7+ years’ experience in performing quantitative analysis, statistical modeling, loss forecasting, loan loss reserve modeling, and particularly econometric modeling of consumer credit risk stress losses
- At least 4 years’ experience in developing credit risk/marketing scorecard with 2 experience in leading a risk model development
- Hands on experience of Risk Model Development procedures and concepts
- Experience with dynamics of unsecured products 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, and model production implementation)
- Ability to manage work in cross functional teams, including country/region’s business stakeholders, model validation and governance teams, and model implementation team
- Good understanding of regulatory requirements
- Exposure to various stress loss modeling approaches at the segment or account level preferred
- Able to communicate technical information verbally and in writing to both technical and non-technical audiences
- Strong technical skills in modeling procedures is required (regression, time series, decision tree, linear/nonlinear optimization etc.)
- Proficiency in SAS/SQL/Oracle/Unix/Microsoft Word, Excel and PowerPoint
- Basic programming skills in Python or R is required
- Strong communication skills to present technical information verbally and in writing to both technical and non-technical audiences is required.
- Ability to influence others in technical matters is required.
- On-the-job Python coding experience is preferred.
- Machine Learning knowledge is preferred
- Big Data concepts understanding is preferred
Job Family Group:
Risk Analytics, Modeling, and Validation
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