Fraud Modelling

Harnham ,
London, Greater London
Job Type: Full-time
Salary: £55,000 per annum

Overview

Fraud Modelling London £55,000 - £85,000 Are you interested in developing a state of the art fraud solution? If so, an exciting fraud software company are looking for someone experienced in fraud strategy with good modelling skills. THE COMPANY Leveraging cloud based technology, this company have developed a unique digital identity solution that scores consumer behaviour, allowing their clients to grow as sustainable and trusted businesses. You will have access to data from some of the largest Financial Services and e-Commerce firms, whilst working alongside a diverse team of strong academics and data-focused minds. You will need a drive to be the best, and in return will have ample opportunities to progress. The environment is collaborative, close knit, and thrives on innovation. THE ROLE As a Senior figure in the business, your responsibilities will be: To utilise your analytical and modelling experience to improve profitability, reduce losses and develop customer trust Provide strategic advice for solution enhancement, backed up by statistical and machine learning techniques Work closely with data scientists, analysts, and client managers to optimise client platforms Test and tune risk models and rules Build scorecards and deliver a world class fraud solution Explain behavioural patterns to technical and non-technical audiences Be a Digital Fraud Risk SME YOUR SKILLS & EXPERIENCE This role would suit someone with: Experience working in the financial services industry in a Fraud Strategy Analytics, Decision Science or similar role Strong data analysis techniques and an interest in machine learning A specialism for fraud or credit risk strategy development Coding experience in SQL, SAS, Python, or R Experience with PySpark or sklearn is advantageous A good degree in a Mathematical, Statistical or similar discipline BENEFITS £55,000 - £85,000 Competitive bonus Company days out Health insurance Matched pension contribution HOW TO APPLY Please register your interest by sending your CV to Rosalind Madge via the Apply link on this page