Senior Quantitative Analyst

2 days ago

Bikaner, Rajasthan, India beBeeCreditRisk Full time ₹ 90,00,000 - ₹ 1,20,00,000
Quantitative Risk Modelling Expert

Our team seeks an analytical expert to lead risk modelling initiatives.

This role involves developing and refining quantitative models that support credit rating decisions, risk assessments, and financial forecasts.

  • 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.
  • 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.
  • 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.
  • 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.
  • Liaise with cross-functional teams including Ratings, IT, Compliance, and Data Engineering.
  • Provide analytical support during credit rating committee discussions and reviews.

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.

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