Analyst - Payments Fraud

Are you passionate about combating fraud and protecting users from sophisticated threats? As Spotify continues to grow and innovate, we are looking for a dedicated Fraud Analyst to join our Commerce Fraud Operations team. This is your chance to play a crucial role in enhancing our fraud prevention strategy, ensuring the safety and integrity of our platform. If you have a keen eye for detail, strong analytical skills, and a drive to stay one step ahead of fraudsters, we want to hear from you!You will work with a global team of world-class business managers, data scientists, product managers and engineers. We are all passionate about what we do and move forward with high impact projects at a high pace. Learning and improving is part of our daily routine, and you will be free to develop your skills and ways of working. Our collaborative environment encourages innovation and continuous improvement, making it an exciting place to grow your career.

What You'll Do

Review suspicious activity flagged by our fraud system and take mitigating and preventative action to protect our genuine users and revenue. Be creative and proactively seek out new and unknown fraud and abuse trends. Present your findings and apply your expertise to suggest improvements to controls and processes. Work closely with our Data Science, Engineering, and Product teams to influence and implement system changes in response to evolving fraud trends. Continuously seek to enhance our setup by researching new technologies and methods in fraud prevention, thereby expanding our team's capabilities and improving our fraud prevention efforts. Handle daily fraud and abuse related processes, escalations and alerts. Support the Fraud Operations Lead in maintaining and improving internal policies, processes and procedure documentation. Assist with ad hoc queries and provide analytical support to the wider fraud team.

Who You Are:

2+ years experience in a fraud analyst role, preferably a merchant fraud role. Familiarity with common fraud prevention techniques and emerging industry trends. Direct experience working with machine learning and rule-based fraud prevention tooling (such as Ravelin/Sift/Signifyd/Accertify etc) Proficiency with data analysis using SQL. Knowledge of Google BigQuery is a plus. Experience with a dashboard visualization tool such as Looker, Tableau or similar. An ambitious and creative thinker who works independently solves vague problems, and translates complex ideas into practical applications for various audiences. A communicative and collaborative person with experience in building and maintaining strong relationships with internal stakeholders, operations and partners.

Where You'll Be

You'll be based in London, UK.