The Financial Crime Data Analytics will be instrumental in developing cutting-edge data-driven solutions that strengthen the clients financial crime detection and prevention capabilities.

Key Responsibilities:

• Design and implement innovative data analytics methodologies to reduce false positives and enhance transaction monitoring efficiency.
• Extract, validate, and transform data from multiple internal sources to support robust financial crime analytics.
• Analyse emerging financial crime patterns and proactively develop detection scenarios using advanced analytics tools.
• Assess AML/CFT typologies and transaction monitoring configurations to ensure optimal system performance.
• Maintain and enhance compliance systems and proactively address data quality issues.
• Develop insightful dashboards and KPIs to provide performance analytics for the Financial Crime team and senior leadership.
• Translate analytical insights into actionable recommendations communicated across departments.
• Pro-actively manage data quality issues.
• Lead the consolidation and reporting of key compliance and risk metrics.

Ideal Candidate:

• Bachelor’s degree in Computer Science, Statistics, Mathematics, or a related field.
• Proficient in analytics and BI tools (e.g., SAS, SQL, Power BI).
• Minimum of 5 years’ experience in the banking or financial services industry, with deep knowledge of financial crime compliance and analytics.
• Expertise in a range of analytical techniques, including machine learning.
• Strong communication skills with the ability to present complex data insights to senior management.
• Experience in data visualisation and team leadership.