Data Scientist (Fraud)

Overview

Data Scientist (Fraud) role focused on building ML models, experiments, and fraud detection systems.

What you'll do

• Prototype, evaluate, and help produce machine learning models for fraud detection.
• Own ongoing monitoring and retraining cycles for fraud models.
• Design and run experiments to measure impact of fraud interventions.
• Size fraud typologies across product lines to inform prioritization and investment decisions.
• Build and maintain anomaly detection systems to surface novel fraud vectors.
• Partner with fraud ops, engineers, product managers, and analysts to turn model outputs into mitigations.

What you'll need

• 3+ years of experience in data science, decision science, or risk analytics in fraud/payments/financial crime.
• A degree in a quantitative field (Statistics, Mathematics, Engineering, Computer Science, or similar).
• Hands-on experience building and deploying ML models in a production environment.
• Solid grounding in experimentation, statistical inference, model evaluation, and feature engineering.
• Proficiency in Python and SQL across the full model development lifecycle.
• Ability to communicate technical findings to non-technical stakeholders and translate insights into action.

Details

• Work mode: Remote.
• Location: Poland.