Job Openings
Financial Crime Data Services Analyst
About the job Financial Crime Data Services Analyst
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