Machine Learning Lead

You will own the fraud and risk intelligence layer, lead the first dedicated machine learning team, and build production fraud models using transaction and behavioral data. You will manage the model lifecycle, define risk metrics, integrate external fraud partners, establish ML practices, and shape the fraud and risk roadmap.

Responsibilities

• Strengthen fraud detection and risk decisioning
• Perform feature engineering and model development
• Deploy fraud models to production
• Own experimentation, evaluation, monitoring, and iteration across the model lifecycle
• Define and track fraud and risk metrics
• Explore transaction and behavioral data for fraud signals and attack patterns
• Partner with Engineering, Product, and Operations
• Integrate and orchestrate external fraud and risk partners
• Establish ML and data practices
• Shape the fraud, risk, and ML roadmap

Requirements

• 5+ years in machine learning, applied data science, or production ML
• Experience building fraud models on the acquiring side of payments
• Experience taking ML projects from proof of concept to production
• Knowledge of authorization fraud
• Knowledge of card-not-present fraud
• Knowledge of friendly fraud
• Knowledge of chargeback patterns
• Knowledge of merchant risk
• Machine learning
• Statistics
• Feature engineering on high-volume financial data
• End-to-end problem ownership
• Cross-functional collaboration
• Acquirer, ISO, PayFac, or payments infrastructure experience preferred
• MLOps pipeline and monitoring experience preferred
• Cloud compute experience preferred
• Card network rules and dispute workflows preferred
• Real-time fraud scoring experience preferred
• Stablecoin, crypto, or alternative payment rails experience preferred

Benefits

• Performance bonus
• Equity grant
• Health and wellness benefits
• 401(k) savings plan
• Flexible time off