🛠 Tech Stack

💼 About This Role

You'll architect real-time defense strategies for a digital payment platform used by 6 million users. Your work will directly reduce fraud losses while maintaining a frictionless user experience. You'll collaborate with Data Science and Engineering to operationalize machine learning models in real-time decisioning.

🎯 What You'll Do

• Design and deploy real-time fraud decisioning logic combining ML scores and velocity features
• Translate fraud patterns into high-performing rules balancing false positives and losses
• Proactively hunt for emerging fraud schemes and develop mitigation strategies
• Partner with Product and Engineering to define analytical requirements for new features

📋 Requirements

• 3-7 years of experience in risk, payments, or credit sectors
• Highly skilled in SQL and Python for data analysis
• Solid understanding of payment fraud dynamics and real-time decisioning environments
• Excellent communication skills and fluency in English

✨ Nice to Have

• Experience with Machine Learning or Data Science
• Knowledge of PySpark or GraphQL

🎁 Benefits & Perks

• ❤️ Health (Private insurance, psychological support, mental health workshops)
• 💰 Financial resources (Stock Option Plan, Meal vouchers, Relocation support)
• ⚙️ Growth and development (Professional development programs, Language courses)
• 🌱 Flexibility (Unlimited PTO, Hybrid working, Flexible hours)
• 👨‍👩‍👧 Family (Enhanced parental leave, Additional leave for child sickness)

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3Hiring Manager Interview· 45 min