data analyst in payment fraud

Satispay is building a financial platform that makes financial services easy and accessible for over 6.5 million users. The company started with payments and has expanded into benefits, investing, and cards.

• Architect and deploy real-time decisioning logic combining ML scores with velocity features;
• Translate complex fraud patterns into high-performing rules while balancing False Positive Rates and Gross Fraud Loss;
• Hunt for emerging fraud schemes, including ATO and social engineering, and develop end-to-end mitigation strategies;
• Partner with Product and Engineering to define analytical requirements for new features and third-party data signals;
• Work with Data Science to operationalise machine learning models and combine model scores with heuristic rules;
• Analyse security measures and design dynamic friction strategies for a seamless user experience;
• Monitor rule efficacy and portfolio health;
• Present data-driven recommendations to senior leadership to evolve risk appetite.

• 3–7 Years of professional experience in risk, payments, or credit;
• Strong SQL and Python skills for data analysis and strategy development;
• Solid understanding of payment fraud dynamics;
• Experience working with real-time decisioning environments;
• Excellent communication skills;
• Fluent English;
• Nice to have: Experience with Machine Learning, Data Science, PySpark, or GraphQL knowledge.

• Private insurance for the employee and family;
• Psychological support with Serenis and mental health workshops;
• Stock Option Plan;
• Meal vouchers;
• Relocation support if moving countries;
• Professional development programs;
• Internal mobility;
• Language courses with Preply;
• Unlimited PTO;
• Flexible working hours;
• Three days per week in-office, with the option to request extra remote time;
• Enhanced parental leave;
• Additional leave for child sickness.