Role overview:
The role supports Financial Crime Intelligence, Investigations & Analytics by leveraging expertise in data interpretation, visualization, and statistical analysis to turn data into actionable insights. It will support finetuning of CFCC systems, cross-jurisdictional special investigations, and operational and strategic intelligence through the analysis of data. Finally, the role shall support the Group’s risk culture and profile by contributing data for financial crime related staff awareness and thought leadership.
Job responsibilities:
Collect, clean and analyze large datasets to identify patterns and trends related to financial crime.
Develop and maintain dashboards and reports using visualization technologies such as Qlik Sense, Power BI, or similar tools to monitor key performance indicators and detect suspicious behaviour.
Collaborate with stakeholders to understand business requirements and provide data-driven recommendations.
Conduct ad-hoc analyses and present findings to support decision-making processes, especially the finetuning of FC risk systems and reengineering of FC risk processes.
Ensure Financial Crime risk data accuracy and integrity through rigorous validation and testing.
Provide input to and own the design of Financial Crime Risk Update to all staff and related thought leadership materials, and collaborate with relevant stakeholders for their distribution.
Qualifications
Qualifications and Experience:
Bachelor’s or Master’s degree in statistics, mathematics, computer science, economics, or a related field.
Relevant professional qualifications such as CAMS, ICA will be an advantage.
5+ years of relevant professional experience
Competencies:
No less than 5 years of compliance or risk management experience, with significant portion within a large international bank.
Strong understanding of Regulatory Compliance and requirements within the banking industry.
Proven experience working within Risk and in data analysis, preferably within the financial services industry or related fields.
Proficiency in data manipulation and analysis using tools such as SQL, Python, R, or similar.
Strong analytical and problem-solving skills with attention to detail.
Clear communication skills to convey complex findings to stakeholders and fluency in English.
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