Join us as a Fraud Prevention Data Analyst     You’ll apply a data driven approach to identify, assess, mitigate, monitor and report on fraud risk so we can manage any threat of fraud  Importantly, you’ll also monitor and evaluate the performance of our fraud prevention processes and strategies  This is a critical role where you’ll be responsible for promoting a culture that helps us manage fraud risk effectively within the business     What you'll do      In your new role, you’ll assess and understand external fraud risks associated with our business activities, while reviewing and developing processesto help mitigate those potential fraud risks.     You’ll also:     Evaluate new data sources and integrate them into our existing strategies, so we can optimise our ability to prevent fraud activity Provide ongoing, in-depth analysis that will identify existing and emerging fraud trends which will influence business decision making   Build and maintain strong internal and external business relationships, sharing information and data to enhance our fraud prevention capability  Demonstrate subject matter expertise which will lend itself to the development of new products, systems and processes across the business      The skills you'll need      We’re looking for someone who has strong technical and numerical skills, with experience in using risk management tools and techniques fraud profiling score systems, data modelling, data mining and behavioural scoring systems.  As well as this you'll also have proven experience in developing fraud strategies utilising fraud profiling tools such as Falcon, Arcot, Threatmetrix or ARIC.   You’ll also have:     Proven experience in applying statistical modelling and evaluation techniques to the development of fraud risk prevention strategies Proficiency in data manipulation tools such as SAS, SQL, Python or similar A degree level qualification in a numeric discipline like Mathematics, Statistics or Operational Research   Strong database management skills and other programming languages,and proven experience in interpreting management information (MI) Experience of data visualisation tools such as Tableau