Staff Data Scientist - Fraud & Risk

📋 Description

• Design and implement deep learning models (Transformers, CNNs/RNNs, graphs) for fraud.
• Build and optimize models with tabular data, text, point clouds, and images.
• Lead end-to-end ML lifecycle: exploration, feature engineering, training, evaluation, deployment, monitoring.
• Own outcomes, data quality, and delivery timelines; escalate issues as needed.
• Mentor peers and junior data scientists; foster experimentation and learning.
• Collaborate with Product, Engineering, and Risk to define data needs and guide decisions.

🎯 Requirements

• Master’s or PhD in CS, Statistics, Applied Mathematics, Data Science, or related field; or equivalent professional experience.
• 8+ years in data science/ML; fintech/high-growth tech preferred.
• Experience in fraud prevention, risk modeling, or identity verification.
• Hands-on with deep learning models (Transformers, CNNs/RNNs, graph learning).
• Proficient in Python, SQL, PyTorch, TensorFlow, scikit-learn.
• Model deployment and monitoring in production; real-time inference a plus.

🎁 Benefits

• Equity compensation
• Bonus opportunities
• Remote-first environment
• Career growth and mentorship