Assistant Manager/Manager - Model Risk Management/Credit Risk - SAS

Looking for professionals having minimum 2.5 years of experience in credit risk domain, has worked on model development, model validation, model monitoring with strong hands on expertise in SAS.

Job Description

- Model Risk Management (MRM) is an independent oversight function. The Bangalore center is one of the five MRM locations across the globe and is responsible for development and maintenance of Model Risk Management Policy and procedures, for evaluation and approval of very high, high and medium high risk models used in global consumer risk management.

- The position will be part of the Model Risk Management, India (Bangalore) team. His/her primary role is to evaluate conceptual soundness and model performance of loss forecasting, balance forecasting, stress testing, PPNR, Loan Loss Reserves (LLR), and macro-economic forecasting models that are developed by other Global Consumer Teams as part of Citi's Comprehensive Capital Analysis and Review (CCAR) submissions.

- The roles are very critical to the organization, as MRM's authorization on the use of the CCAR models are based on the reviewer's evaluation results. The reviewer will adhere to the Model Risk Management Policy when evaluating models and ensure models, documentation, and monitoring MIS are compliant with applicable policies.

Key Responsibilities:

- Review and validate new and existing model and framework, provide effective challenge, ensure validation work quality.

- Help manage model risk across the model lifecycle including model validation, performance evaluation and annual model reviews.

- Challenge and continually improve MRM Guidance on modeling approaches and model performance testing.

- Contribute to strategic, cross-functional initiatives within MRM organization.

- There will be plenty of learning and growth opportunities with this position, from both technical and leadership perspective. The incumbent will be exposed to different areas of business operations and a variety of modeling approaches, including machine learning on top of industry standard tools.

Qualifications

- Minimum of Master's degree in a quantitative field (Statistics, Mathematics, Physics, Engineering, Computer science, etc.)

- Higher academic qualifications and/or certifications such as a PhD, a second Master's degree, CPA or CFA is a plus

- Must have a strong background in statistical modelling techniques.

- Good understanding of Model Risk Management.

- Strong written and oral communication skills.