2 of 2 Remote Fraud Data Analyst Jobs in the UK

Social network you want to login/join with: Join Marcura as Fraud Data Analyst – A Remote First Opportunity with Flexible Work Culture About Us Marcura was founded 23 years ago by two visionary entrepreneurs. Our mission has always been to revolutionize digital processes within the global shipping industry. We achieve this by putting our customers first … for continued success. Now, we’re looking for talented individuals who are as committed to excellence as we are to join us in this exciting journey. About the Role: Fraud Data Analyst As a Fraud Data Analyst, you will play a critical role in detecting, analysing, and mitigating fraudulent activities across card and wire … You will work closely with the Transaction Monitoring Manager and the broader Compliance team to ensure the integrity and security of our payment systems. Your role will involve leveraging data analytical skills, Python, SQL, and various analytical tools to identify suspicious activities, enhance fraud detection strategies, and support decision-making processes. Your new day-to-day will involve More ❯

so that we're able to interact and collaborate in person. In Technology, we're asking that you attend the office a minimum of 1 day per week. Our Data Environment Our Data teams are excited about the value of data within the business, powers our product decisions to improve things for our customers and enhance effective … what their primary tech stack may be. Hear from the team in our latest blogs or our case studies with Women in Tech . We are looking for talented data professionals at all levels to join the team. We value people being engaged and caring about customers, caring about the code they write and the contribution they make to … to a multitude of problems and challenges, who can work across teams do great things here at Starling, to continue changing banking for good. Responsibilities: Work closely with the Fraud Strategy and Change, Fraud Risk, and Engineering teams to identify push payment fraud trends and use data analysis to propose solutions for prevention and transaction monitoring. More ❯