Senior Quantitative Analyst

18 hours ago

Bareilly, Uttar Pradesh, India beBeeCreditRisk Full time ₹ 2,00,00,000 - ₹ 2,50,00,000

Are you a seasoned data analyst looking for a new challenge? We have an exciting opportunity for a Credit Risk Modelling Lead Analyst to join our team.

Job Description

This role involves building, validating and enhancing quantitative models that support credit rating decisions, risk assessments and financial forecasts. You will design, implement and refine statistical and econometric models to support credit rating methodologies.

  • 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).

Key Responsibilities include:

  • Model Development & Enhancement:
    • Develop and enhance quantitative models to support credit rating decisions.
  • Model Validation & Monitoring:
    • Conduct performance testing, benchmarking and sensitivity analysis of existing models.
  • Data Analysis & Management:
    • Work with large datasets from multiple sources to support model calibration and back-testing.
  • Documentation & Communication:
    • Prepare comprehensive model documentation for internal committees and regulators.
Candidate Requirements
  • Bachelor's Degree in Commerce / Finance / Statistics / Mathematics / Data Science or related field.
  • Master's Degree in Finance / Statistics / Mathematics / Data Science or related field (Preferred)
  • 3-5 years of experience in credit risk modelling, model validation or quantitative analysis within a financial or ratings environment.
  • Strong command of programming tools including Python, R, SAS and SQL.
  • Practical understanding of credit risk models, financial instruments and portfolio risk dynamics.
What We Offer
  • Competitive salary and performance-based bonus.
  • Professional growth in a dynamic, intellectually rigorous environment.
  • Exposure to cutting-edge credit risk modelling practices.

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