At Preply, we’re all about creating life‑changing learning experiences. We help people discover the magic of the perfect tutor, craft a personalised learning journey, and stay motivated to keep growing. Our approach is human‑led, tech‑enabled, and we’re creating real impact. We’ve reached unicorn status with a $150M Series D, accelerating our vision to transform education through human‑led, AI‑enhanced learning. 100,000+ tutors teach 90+ languages to learners in 180 countries, and we’re only getting started.

What You’ll Be Doing

- 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

What You Need To Succeed
- 4+ years of experience in fraud analytics, risk analysis, or a closely related payments/trust & safety domain
- Strong SQL and Python proficiency, 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

Nice to have
- Prior experience working in a marketplace or two‑sided platform
- Experience with

📌 Senior Data Analyst - Fraud Prevention (Barcelona)
🏢 Preply
📍 Barcelona