preply - Senior Data Analyst - Fraud Prevention
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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 • Prior experience working in a marketplace or two-sided platform. • Experience with payment processing concepts - chargebacks, dispute flows, authorisation rates, PSP dynamics. • Exposure to compliance or regulatory frameworks (PSD2/3, AML, KYC).
Responsibilities
• 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.
Benefits
• An open, collaborative, dynamic and diverse culture; • A generous monthly allowance for lessons on Preply.com http://preply.com, Learning & Development budget and time off for your self-development; • A competitive financial package with equity, leave allowance and health insurance; • Not in Barcelona? We offer an 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;
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