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