• The Manager of Advanced Risk Data Analytics is responsible for the implementation of advanced risk data analytics strategies. This role involves managing complex data analysis projects, developing predictive models, and providing insights to support risk management decisions. The ideal candidate will have a strong background in data analytics and risk management

Job Responsibilities/ Accountabilities/ Operational Efficiency:

• Advanced Data Analytics:
• Develop and implement advanced data analytics frameworks and methodologies for all principal risks.
• Develop designs for models, smart rules and analytics for Fraud Risks across the group and all operating subsidiaries.
• Support designing new use cases, rules adjustments and new integrations to the analytics risk management tools
• Analyze large and complex datasets to identify risk exposures and trends.
• Utilize machine learning and statistical techniques to develop predictive models to support both non-financial 
• Provide actionable insights and recommendations to senior management based on data analysis.
• Risk Management:
• Collaborate with risk management teams to integrate data analytics into risk assessment processes.
• Conduct regular reviews and stress testing of risk management models to ensure their accuracy and reliability.
• Develop and maintain risk dashboards, heat maps and reporting tools.
• Regulatory Compliance:
• Ensure compliance with regulatory requirements and internal policies related to data analytics and risk management.
• Stay updated on regulatory changes and industry best practices.
• Planning:
• Input to the development of the organization’s risk management strategy.
• Provide insights and recommendations to support decision-making processes.
• Collaborate with other departments to integrate risk management practices into their operations.
• Reporting and Communication:
• Prepare and present risk analysis reports for senior management.
• Communicate complex risk concepts in a clear and concise manner to stakeholders. 

Required Skills and Qualifications

• Education: A degree in  technology, Data Science, Statistics, Finance, Economics, or a related field. 
• Technical Skills: Proficiency in statistical software e.g., SAS, R, Python, data visualization tools e.g., Tableau, Power BI, and risk management software.
• Certifications: Professional certifications such as FRM Financial Risk Manager, PRM Professional Risk Manager, CISA, CAMS or ACFE are highly desirabl