Job Description

You will be responsible for developing and maintaining quantitative risk models for both financial and non-financial risks in the company. You will use advanced analytical techniques to interpret large datasets, identify trends, and provide data-driven insights that support risk management decisions and to ensure regulatory compliance. You will also work closely with the internal data team or external consultants in developing AI tools for use case in risk & compliance. The ideal candidate has strong quantitative skills, technical expertise in statistical software, and the ability to communicate complex information to both technical and non-technical stakeholders.

Job Responsibilities:

Risk modelling

• Maintain and enhance models for assessing various types of risk, including stress test models, ALM models, liquidity risk model, and credit risk model.
• Conduct regular validation, model performance monitoring, and benchmarking of models to ensure accuracy, reliability, and regulatory compliance.
• Ensure clear and comprehensive documentation of model methodologies, assumptions, and results in accordance with internal standards and regulatory requirements.

Risk Management Innovation

• Use data analytics / machine learning to improve management of non-financial risks, e.g. trending / indicators of operational risks, sales conduct / behaviour, detection of fraud / misconduct, etc.
• Work with internal and external teams in projects using AI or Generative AI tools to improve efficiency in risk & compliance works.

Collaboration and communication

• Cross-functional collaboration: Work closely with stakeholders from business units to understand business needs and integrate business insights in risk models.
• Communication: Clearly and effectively communicate complex risk assessments and model findings to both technical and non-technical audiences.
• Strategic recommendations: Provide data-driven recommendations to help leadership make informed decisions and develop strategies for risk mitigation

Job Requirements

• Bachelor's or Master's degree in a quantitative field such as Finance, Economics, Statistics, Mathematics, or Data Science.
• Proficiency in programming languages like Python, R, or SAS for statistical modelling and data analysis.
• Knowledge of SQL for data extraction and manipulation.
• Experience with Prophet ALS would be a plus.
• Familiarity with various modelling techniques, including regression analysis, time series, and machine learning.
• Industry knowledge: basic understanding of risk management principles, regulatory frameworks (e.g., MAS RBC2) and financial markets is highly desirable.
• Strong communication and interpersonal skills.
• Excellent attention to detail and critical thinking abilities.
• Ability to work both independently and collaboratively in a fast-paced, dynamic environment
• Professional certifications such as FRM, CFA, or actuarial qualifications are a plus.
• Experience with IFRS17 is preferred.