Work with outputs from ML models to maintain and improve fraud prevention decision, balancing detection coverage against false positive rates
Own the fraud rule lifecycle
designing, testing, and maintaining prevention rules, with a clear view of coverage, false positive trade-offs, and when to retire what's no longer working
Partner with Fraud Operations to understand emerging abuse patterns and translate operational observations into analytical improvements.
Design and maintain alerting systems that identify threats early, giving the team time to respond before incidents escalate.
Forecast fraud losses and chargeback volumes, giving Finance and Risk leadership earlier visibility into projected exposure.
Define and own the north star metrics and KPIs for fraud prevention, ensuring reporting is clear, owned, and actionable at the executive level.
Act as the data bridge between Product and the Applied AI team
providing performance feedback that informs model updates and roadmap prioritisation.
Support the evaluation of third-party fraud prevention providers, bringing data-driven criteria to vendor assessments.
Collaborate with Data and Analytics Engineering to ensure fraud-related data is tracked, governed, and handled in line with PII requirements.

4+ years of experience in fraud analytics, risk analysis, or a closely related payments/trust & safety domain.
Strong SQL and Python proficiency being comfortable writing analytical queries across large transactional datasets, building monitoring logic, and applying statistical techniques to fraud and risk problems
Experience designing and maintaining dashboards or alerting systems with clear signal-to-noise discipline.
Strong analytical communication: able to turn ambiguous fraud signals into crisp, actionable narratives for operational and executive audiences.
Experience collaborating with cross-functional teams including Operations, Engineering, and Product.
Ability to leverage AI tools and agents as a force multiplier for analysis, while maintaining the critical thinking to interrogate outputs, spot gaps, and own the conclusions
Experience mentoring junior and mid-level analysts helping them grow their technical skills, develop analytical judgement, and raise the quality of the team's output

A generous monthly allowance for lessons on Preply.com
Learning & Development budget and time off for your self-development
A competitive financial package with equity, leave allowance and health insurance
Attractive relocation package to join us in our Preply Barcelona Hub
Access to free mental health support platforms
Access to Gympass-partnered wellness and gym centers throughout Spain to promote and support well-being and physical health

Senior Data Analyst – Fraud Prevention

Key skills