Job Description
We're Hiring | Manager Credit Risk Analytics & Modelling
We are looking for an experienced Manager Credit Risk Analytics & Modelling to join our Risk Modelling team. This is an excellent opportunity for professionals with strong expertise in credit risk assessment, statistical modelling, and team leadership.
Company: INFOMERICS Valuation and Rating Limited
Location: Mumbai & Delhi
Experience: 3 to 6 Years
Open Positions: 3 openings at each location
Key Responsibilities: -
- Develop and enhance general and sector-specific credit risk assessment models.
- Build and maintain Excel-based risk models using statistical techniques and expert judgment.
- Perform model validation using quantitative measures such as Gini Coefficient, Confusion Matrix, Cumulative Default Rates (CDRs), and Rating Transition Rates.
- Recalibrate and review existing models based on validation outcomes, statistical analysis, and AI/ML techniques.
- Conduct benchmarking using internal and external databases such as Capitaline and CMIE Prowess.
- Prepare model documentation, user manuals, and presentations for senior management and committees.
- Coordinate with technology vendors for model implementation, configuration, and User Acceptance Testing (UAT).
- Support regulatory inspections by preparing model-related documentation and responses.
- Mentor, guide, and manage team members while driving performance and development.
- Conduct training sessions for internal stakeholders on rating models.
Qualifications: -
- Master's degree in a relevant discipline.
- CA ,CFA or FRM (completed or pursuing) will be an added advantage.
Skills Required: -
- Strong understanding of corporate credit risk assessment and credit rating methodologies.
- Advanced Microsoft Excel skills.
- Good knowledge of statistical modelling techniques.
- Exposure to AI/ML techniques is preferred.
- Excellent analytical, communication, and leadership skills.
Interested candidates or references may share their updated resume at:
Email: chintan.upadhyay@infomerics.com
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