Financial Crime Data Services Analyst in Bradford

Support the Groups Financial Crime Risk Management Framework & broader Society by supporting the requirements for advanced data mining, statistical analytics and financial crime risk model development.

The Role:

• Lead the production of statistical analysis, modelling and predictive analytics including supervised and unsupervised techniques
• The ability to identify and communicate often complex data and analytical solutions to the wider department, ensuring transfer of key findings to inform business changes and risk mitigation
• Support the Financial Crime management information analysts with smarter trend, insight and complex analysis
• Establish a knowledge of financial crime systems and controls used by the Group, allowing for continuous improved performance
• Use data driven reporting benchmarking across sites to identify best practice and outliers, identifying opportunities for efficiency, forecasting, service, scalability, reducing cost and risk
• Utilise best practice statistical, analytical and modelling techniques to perform complex analysis of the Groups Financial Crime Risks, to enable proactive prevention and detection, optimised tuning of financial crime technologies
• Communicate results of analysis to a high standard, both written and verbally, making recommendations for risk mitigation within risk appetite
• Support the development of the financial crime function in relation to specialist data training, techniques and analytics modelling

The Candidate:

• Ability to apply themselves to problem solving and analysing situations, delivering practical and compliant financial crime controls/solutions
• Evidence of professional learning and development to build and maintain skills and expertise
• Excellent knowledge of supervised and unsupervised modelling technique, using of Python or R
• Ability to carry out statistical analytics and model deployment
• Experience SAS / SQL for dealing with complex data sets / large sets of data
• Able to showcase feature engineering and importance

Desirable:

• Related financial crime qualifications.
• Subject matter expertise in financial crime risk including experience of AML, KYC, Sanctions and Fraud retail banking products and the UK regulatory environment