Job Description
Function description
Your core responsibilities will include:
Stakeholder Alignment & Communication
Coordinate input from IT, Data Hub, Compliance (CPL), and Operations, ensuring alignment through structured documentation, workshops, and clear communication.
Translate complex business requirements into actionable data solutions, balancing technical feasibility with regulatory and operational needs.
Data Governance & Quality
Establish and enforce data governance frameworks, including role definitions, quality rules, and access protocols, in collaboration with data providers and consumers.
Monitor, refine, and escalate data quality issues proactively, ensuring long-term integrity of AML-related datasets (e.g., Customer/Account/Transaction (CAT) data).
Define and document business and technical rules for data integration, ensuring traceability and compliance.
Data Analysis & Troubleshooting
Investigate and resolve data discrepancies, including mainframe-based data points (willingness to explore raw data is essential).
Analyze AML Transaction Monitoring data, identifying patterns, gaps, or anomalies that impact compliance or operational efficiency.
Solution Design & Industrialization
Design logical and physical data models (e.g., data warehouses, datamarts) optimized for AML reporting and analytics.
Develop and industrialize data pipelines, ensuring seamless flow and accessibility across the enterprise.
Prototype solutions to validate business requirements and refine designs based on feedback.
Process Optimization
Streamline data workflows to maximize reusability and efficiency, reducing redundancy and manual interventions.
Advocate for best practices in data security, architecture, and compliance, aligning with IT and risk management standards.
Education
You have at least a Master's degree in a quantitative discipline, such as statistics, mathematics or engineering.
Candidates with other academic backgrounds with substantial knowledge of analytics are also encouraged to apply.
Technical Experience
Mandatory
2–6 years of hands-on experience in Data Analytics, with a focus on KYC/AML processes or financial crime prevention.
Proficiency in SQL and data modeling tools (e.g., PowerDesigner or equivalent)
Preferable
Experience with reporting/dashboard tools (Tableau, BO, SAS, etc.)
Business Experience
Mandatory
Familiarity with Agile methodologies and project management tools (JIRA, Agile Central)
Deep understanding of banking data, particularly AML Transaction Monitoring data (CAT datapoints: customer, account, transaction attributes).
Proven ability to capture, document, and manage functional/non-functional requirements for data solutions.
Knowledge of data security, IT architecture, and financial services operations.
Hands-on experience with data quality frameworks, including rule definition, monitoring, and issue escalation
Soft Skills
Proactive and entrepreneurial mindset—able to drive initiatives independently while collaborating across teams.
Strong analytical and problem-solving skills, with attention to detail and a quality-focused approach.
Adaptability and eagerness to learn, with the ability to connect strategic goals to operational execution.
