Data Scientist - Fraud
- Location
- City Of London, England, United Kingdom
models Utilise and blend all available data sources to ensure all fraud models are highly predictive and market leading - consumer bureau data, postcode insights, open source data,transactional insights & fraud indicators from partnerships Apply traditional model development techniques and approaches (e.g. logistic regression) as well as adopting … Banking, Lending, Insurance, Public Sector, Utilities, etc. Use of LLMs to improve efficiencies in the model building process Use of alternative data such as open banking transactional data in statistical models Experience of working in a product development environment Experience with industry related fraud prevention tools (e.g. Hunter, Kount ...