Senior Quantitative Analyst
4 weeks ago
Credit Risk Modelling Leadership
The role requires a deep technical expertise in credit risk modelling and the ability to lead a team in developing cutting-edge models that meet regulatory and risk management needs.
Key Responsibilities
- Develop advanced credit risk models for provisioning/capital requirements (IFRS CECL BASEL IRB) and internal risk management using statistical econometric and machine learning techniques.
- Apply machine learning algorithms and advanced statistical techniques to enhance model performance.
- Utilise big data technology for data processing and feature engineering.
- Integrate external data sources to improve model accuracy.
- Manage a team of quantitative analysts providing technical guidance and mentorship.
- Collaborate with IT and data engineering teams to ensure availability and quality of data for model development.
- Communicate lucidly model performance and risk assessments to senior management.
Regulatory and Stakeholder Engagement
- Engage with regulatory/statutory bodies to ensure models meet compliance requirements.
- Engage with model validation team to meet validation requirements.
Qualifications and Experience
- Advanced degree in statistics, mathematics, or quantitative finance.
- Proficiency in Python, data visualisation, and PySpark.
- Deep understanding of machine learning algorithms and statistical techniques.
- 10 years of extensive experience in developing retail credit risk models.
- Experience in areas of IFRS CECL BASEL IRB.
- Experience in managing and leading teams of quantitative professionals.
- Proven track record of deploying machine learning and advanced techniques in model building.
Credit Risk Modelling, Model Building, Risk Modelling, CECL, IFRS, Basel, IRB, Credit Risk Models, Machine Learning, Statistical Modelling
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