Data Scientist (Fraud)

📋 Description

• Prototype, evaluate, and deploy ML models for fraud detection; monitor retraining.
• Design experiments to measure fraud interventions; balance UX and loss.
• Size fraud typologies across product lines to guide priorities and investments.
• Build and maintain anomaly detection systems to surface novel fraud vectors early.
• Collaborate with fraud ops, engineers, PMs, and analysts to implement mitigations.

🎯 Requirements

• Degree in statistics, mathematics, engineering, computer science, or similar.
• 3+ years in data science or risk analytics within fraud, payments, or financial crime.
• Hands-on experience building and deploying ML models in production.
• Fraud, risk, or financial services experience is a plus.
• Strong fundamentals: experimentation, statistical inference, model evaluation, features.
• Comfort in fast-paced, cross-functional teams with ownership.

🎁 Benefits

• Culture: People-first environment where all voices are heard.
• Learning: Emphasis on knowledge sharing and internal technical talks.
• Compensation: Attractive salary, pension, health insurance, bonus, and benefits.