VP Transaction Monitoring Data Analyst

Responsibilities

• Design, develop, and implement statistical, mathematical, and machine learning models to support transaction monitoring and financial crime detection.
• Acquire and collect data from internal databases, external datasets, and real-time feeds, performing necessary cleaning and pre-processing.
• Monitor model performance in real-time to identify potential issues, biases, or emerging risks.
• Lead training and mentoring sessions to uplift machine learning capabilities across the organization.
• Evaluate and pilot emerging technologies and frameworks to ensure the organization remains at the forefront of AI innovation.
• Partner with Technology, Operations, and business stakeholders to align detection analytics with evolving priorities.
• Advise senior management on functional impacts and manage risks through robust assessment and governance.

Requirements

• Proven experience using analytical tools for data exploration, analysis, and visualization.
• Strong coding ability in Python and proficiency in SQL.
• In-depth understanding of Financial Institution data, including customer, account, transactional, and payment flows.
• Solid knowledge of AML, Transaction Monitoring, and financial crime typologies.
• Relevant qualifications in data analytics or a related technical field.
• Familiarity with databases and data transformation processes.

Preferred Qualifications

• Experience working within a regulated business environment with exposure to governance and risk management.
• Knowledge of the Global Financial Crime regulatory framework.

About the Company

Barclays is a leading international financial institution committed to excellence, integrity, and stewardship. Our Financial Crime Analytics team plays a pivotal role in shaping end-to-end detection solutions, helping to strengthen the bank's intelligence-focused approach to managing global financial crime risk.