This role represents a fantastic opportunity for a data-driven Business Data & Systems Analyst to strengthen financial crime and AML detection capabilities within a complex, data-rich environment.
The position is suited to a technical data analyst with strong SQL, data modelling, and Power BI expertise, combined with a practical understanding of the financial crime landscape. The focus is on improving systems, data quality, and detection effectiveness — not investigations or case handling.
Key Responsibilities
*Analyse large, complex datasets using SQL to identify trends, anomalies, and control weaknesses
*Develop Power BI dashboards and reporting to support fraud and AML monitoring
*Optimise transaction monitoring and fraud detection system rules to improve accuracy and efficiency
*Design and maintain data models to support financial crime controls and performance tracking
*Enhance data flows, integrations, and data quality across Financial Crime systems
*Partner with Technology, Risk, and Compliance teams to deliver data-led improvements
*Monitor key metrics and recommend enhancements aligned to risk appetite and regulatory expectations
Experience
*Strong background as a Data Analyst, Systems Analyst, or Business Data Analyst
*Advanced SQL skills with experience handling large, complex datasets
*Proven Power BI (or similar) dashboard development and insight delivery
*Experience improving systems, data quality, or rule-based controls
*Practical understanding of financial crime / AML / fraud prevention environments
Desirable
*Experience with transaction monitoring or rule-based detection systems
*Exposure to AML, KYC, payments fraud, or financial crime controls
*Familiarity with Financial Crime platforms (e.g. ACI PRM, SIRA, ThreatMetrix) or similar tools
*Experience with predictive modelling or machine learning techniques
Salary: £45,000 – £65,000 + benefit. Hybrid, 2 onsite days per week (Warwickshire)
Apply for further job & interview details.
Full UK working rights required (no sponsorship opportunity provided).