Описание
Preply creates personalized language-learning experiences by connecting learners with tutors through a human-led, technology-enabled platform. The company serves learners in 180 countries, with more than 100,000 tutors teaching over 90 languages, and develops AI-enhanced solutions for education.
Задачи
- Work with ML model outputs to improve fraud prevention decisions while balancing detection coverage and false-positive rates
- Own the fraud rule lifecycle by designing, testing, maintaining, and retiring prevention rules
- Partner with Fraud Operations to identify emerging abuse patterns and translate operational observations into analytical improvements
- Design and maintain alerting systems that identify threats before incidents evolve
- Forecast fraud losses and chargeback volumes for Finance and Risk leadership
- Define and own north-star metrics and KPIs for fraud prevention, ensuring clear and actionable executive reporting




- Act as the data bridge between Product and the Applied AI team by providing performance feedback for model updates and roadmap prioritization
- Support the evaluation of third-party fraud prevention providers using data-driven vendor assessment criteria
- Collaborate with Data and Analytics Engineering to ensure fraud-related data is tracked, governed, and handled according to PII requirements

Требования
- 4+ Years of experience in fraud analytics, risk analysis, or a closely related payments or trust & safety domain
- Strong SQL and Python proficiency, including analytical queries across large transactional datasets, monitoring logic, and statistical techniques for fraud and risk problems
- Experience designing and maintaining dashboards or alerting systems with clear signal-to-noise discipline
- Strong analytical communication skills for turning ambiguous fraud signals into clear, actionable narratives for operational and executive audiences
- Experience collaborating with Operations, Engineering, and Product
- Ability to use

📌 data analyst for fraud prevention (Barcelona)
🏢 Enfint
📍 Barcelona