
Senior Quantitative Analyst
6 days ago
We are seeking an experienced and skilled Credit Risk Modelling Analyst to join our team. This role involves developing, validating, and enhancing quantitative models that support credit rating decisions, risk assessments, and financial forecasts.
The ideal candidate will bring a solid foundation in credit risk modelling along with hands-on experience in model development and data analysis within a financial or ratings environment.
Key Responsibilities:
- Design, implement, and refine statistical and econometric models to support credit rating methodologies.
- Build models for key risk parameters, including Probability of Default (PD), Loss Given Default (LGD), and Expected Loss (EL).
- Contribute to the development of macroeconomic scenario analysis and stress testing frameworks.
Model Validation & Monitoring
- Conduct performance testing, benchmarking, and sensitivity analysis of existing models.
- Implement validation protocols to ensure models meet internal standards and regulatory expectations.
- Recommend enhancements based on validation outcomes and business feedback.
Data Analysis & Management
- Work with large, structured and unstructured datasets from multiple sources to support model calibration and back-testing.
- Perform exploratory data analysis and statistical testing to inform model assumptions.
Documentation & Communication
- Prepare comprehensive model documentation for internal committees, model governance teams, and regulators.
- Communicate complex quantitative findings clearly to non-technical stakeholders, including rating analysts and senior management.
Candidate Profile
- Bachelor's Degree in Commerce / Finance / Statistics / Mathematics / Data Science / Computer Engg. / IT / Economics, Chartered Accountant or related field.
- Master's Degree in Finance / Statistics / Mathematics / Data Science / Economics, or related field (Preferred)
- 3–5 years of experience in credit risk modelling, model validation, or quantitative analysis within a credit rating agency, bank, or financial institution.
- Candidates having prior experience of working in a Credit Rating Agency preferred.
- Strong command of programming tools such as Python, R, SAS, and SQL.
- Practical understanding of credit risk models, financial instruments, and portfolio risk dynamics.
- Familiarity with regulatory frameworks like Basel III/IV.
- Excellent quantitative and analytical skills with strong attention to detail.
- Ability to manage multiple projects with minimal supervision.
- Exposure to machine learning techniques applied to credit risk or financial modelling.
- Experience with data visualization tools (e.g., Power BI, Tableau).
- Working knowledge of rating agency methodologies and capital markets.
Why Join Us?
- Be part of a dynamic, intellectually rigorous environment.
- Competitive salary and performance-based bonus.
- Professional growth and exposure to cutting-edge credit risk modelling practices.
We offer a collaborative, diverse, and supportive team culture.
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