Chief Quantitative Analyst

4 days ago

Kurnool, Andhra Pradesh, India beBeeRisk Full time ₹ 1,50,00,000 - ₹ 2,00,00,000
Quantitative Risk Modeler Job

We are seeking an experienced and analytically driven Quantitative Risk Modeler to join our Credit Ratings team. This role involves building, 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:
  • Model Development & Enhancement:
    • 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.
    • 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.

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