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Job Location: Bangalore/Bengaluru
Greetings from CareerNet…!!!
We have a great opportunity with one of our Product based MNC company for PPNR Balance & Loss Forecasting-Analyst II Officer/AM position in Bangalore location.
Interested candidates can share their resume to below email id
Looking after for more Diversity/Female profiles.
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, and macro-economic forecasting models that are developed by other Global Consumer Teams as part of clients Comprehensive Capital Analysis and Review (CCAR) submissions. The roles are very critical to the organization, as MRMs authorization on the use of the CCAR models are based on the reviewers 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.
- 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.
- Minimum of Masters degree in a quantitative field (Statistics, Mathematics, Physics, Engineering, Computer science, etc.)
- Higher academic qualifications and/or certifications such as a PhD, a second Masters 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.