Assistant Manager/Manager - Risk Modeling - SAS/Python/R - BFSI

Looking for professionals with 4-9 years of experience into Risk Modeling, well versed with statistical & machine learning techniques, hands on exp in SAS/Python/R.

Model Risk Management ("MRM") provides oversight for the MRM Framework, which consists of the policy, processes, and procedures.

The validator role will be part of the Consumer Valuation Models group within Model Risk Management. His/her primary function is to conduct validation activities for Consumer risk scoring and segmentation models. The role is very critical to the organization as the authorization on the use of the BAU models is based on MRM's validation results. The member will adhere to the MRM's firm-wide policy, procedures, and guidelines.

Key Responsibilities:

- Conduct validation and ongoing monitoring activities for new and existing models. Provide assessment by writing a comprehensive validation report based on his/her judgment of the validation results

- Provide effective challenge to the model design and construction and conduct incremental analysis and testing as necessary

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

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

- This position provides a very significant amount of learning and growth opportunities 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

- Relevant consumer finance or credit card industry experience to include loss forecasting/stress testing/consumer risk model development, maintenance, tracking and management

- Must have a strong background in statistical modelling techniques.

- Good understanding of Model Risk Management.

- Strong written and oral communication skills.