Quantitative Risk Analyst

1 day ago

Mumbai, Maharashtra, India beBeeRisk Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
Job Title: Quantitative Risk Analyst

The role of Quantitative Risk Analyst is to design, develop, and implement advanced statistical and econometric models that support credit rating decisions. The ideal candidate will have a strong background in quantitative analysis, risk modeling, and programming skills.

About the Role
We are seeking an experienced Quantitative Risk Analyst to join our team. This role involves building, validating, and enhancing quantitative models that support credit rating decisions. The successful candidate will work closely with our credit rating analysts to develop and maintain accurate and reliable credit risk models.

Key Responsibilities
  • Develop and implement statistical and econometric models to support credit rating methodologies.
  • Benchmark and validate existing models to ensure accuracy and reliability.
  • Collaborate with data scientists to design and develop machine learning algorithms for credit risk prediction.

Required Skills and Qualifications
  • Master's degree in Finance, Statistics, Mathematics, Data Science, or related field.
  • 3-5 years of experience in credit risk modeling, model validation, or quantitative analysis within a credit rating agency, bank, or financial institution.
  • Strong command of programming languages such as Python, R, SAS, and SQL.
  • Practical understanding of credit risk models, financial instruments, and portfolio risk dynamics.
  • Familiarity with regulatory frameworks such as Basel III/IV.

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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