We are the leading global information services company, providing data and analytical tools to our clients around the world. We help businesses to manage credit risk, prevent fraud, target marketing offers and automate decision making. We also help people to check their credit report and credit score and protect against identity theft.
We employ approximately 17,000 people in 37 countries and our corporate headquarters are in Dublin, Ireland, with operational headquarters in Nottingham, UK; California, US; and São Paulo, Brazil.
Experian is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, disability, age, or veteran status.
We are looking for Senior Analytics Architect to join our Global Software Group!
Experian® Decision Analytics (DA) integrates predictive data and analytics into valuable business decisions that provide greater insight into decision performance and helps companies keep pace with changing business priorities. By applying expert consulting, analytical tools, software and systems to convert data into valuable business decisions. Our expertise spans a variety of industries and we provide software to some of the world’s largest finance, telcos and other blue-chip companies. The crown jewel in our software suite is PowerCurve which provides best-in-class decisioning applied across the whole customer lifecycle from customer acquisition to in-life and collections, as well as in fraud detection and identity resolution systems. Our development teams are focused on developing innovative, highly customizable and user-friendly decisioning and fraud and identity solutions. Currently we have been promoting a cloud-first approach as we transform to a SaaS model, whilst promoting the integration if Decision and Analytics though an innovative concept based on Machine Learning promoting a comprehensive capability for ML Ops across the entire decision lifecycle: from learning to deployment, benchmarking, governance and continuous improvements.