Staff Data Scientist - Fraud & Risk

Staff Data Scientist leading fraud and risk ML initiatives with advanced deep learning models and multi-modal data, driving end-to-end lifecycle from model development to production monitoring.

• Design, develop, and implement advanced deep learning models including transformers and graph learning for fraud/risk
• Lead end-to-end ML lifecycle from data exploration to deployment and monitoring
• Mentor peers and collaborate cross-functionally to drive initiatives
• Present findings to technical and executive stakeholders
• Stay current with AI advancements and apply innovative approaches

Expertise in Python-based ML stack (PyTorch, TensorFlow, scikit-learn) with experience in transformers, CNNs/RNNs, graph learning, and real-time inference; strong data integration/feature engineering across tabular and unstructured data; production-grade deployment and monitoring.

The ideal candidate is a senior data scientist with 8+ years of experience in deep learning and fraud/risk modeling, proficient in Python and ML frameworks, and comfortable leading cross-functional initiatives and production ML deployments in a fintech setting.