Lead Analyst Specialist

6 days ago

Aurangabad, Maharashtra, India beBeeQuantitativeRiskModeller Full time ₹ 18,00,000 - ₹ 24,00,000

Job Title: Quantitative Risk Modeller

About the Role

We are seeking an experienced and skilled quantitative risk modeller to join our credit ratings team. This role involves developing, validating, and enhancing statistical models that support credit rating decisions, risk assessments, and financial forecasts.

  • This includes designing, implementing, and refining econometric models to support credit rating methodologies.
  • Building models for key risk parameters, including Probability of Default (PD), Loss Given Default (LGD), and Expected Loss (EL).

The ideal candidate will have 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 and implement statistical models to support credit rating methodologies.
    • Build models for key risk parameters, including PD, LGD, and EL.
  • Data Analysis & Management:
    • Work with large 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.

Candidate Profile

  • Bachelor's Degree in Finance, Statistics, Mathematics, Data Science, or related field.
  • Mastery of programming languages such as Python, R, SAS, and SQL.
  • Familiarity with regulatory frameworks and risk management principles.
  • Excellent analytical skills with strong attention to detail.

Benefits

  • 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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