Machine Learning Lead

Responsibilities

• Strengthen fraud detection and risk decisioning capabilities through feature engineering and model development
• Own the full model lifecycle including experimentation, evaluation, monitoring, and iteration
• Define and track core fraud and risk metrics such as detection rate and chargeback rate
• Explore transaction and behavioral data to surface new fraud signals
• Partner with Engineering, Product, and Operations to embed fraud intelligence into payment flows
• Integrate and orchestrate external fraud and risk partners
• Establish the foundation for ML and data practices across the company

Requirements

• 5+ years in machine learning, applied data science, or production ML roles
• Demonstrated experience building fraud models in payments (acquirer, PSP, or payment facilitator)
• Proven track record of taking ML projects from proof-of-concept to production
• Deep familiarity with acquiring-side fraud dynamics and chargeback patterns
• Strong foundation in ML, statistics, and feature engineering on high-volume financial data
• Ability to own ambiguous problems end-to-end

Preferred Qualifications

• Experience at an acquirer, ISO, PayFac, or payments infrastructure company
• Experience developing and scaling MLOps pipelines and monitoring systems
• Experience scoping cloud compute requirements for scalable ML workloads
• Familiarity with card network rules and fraud liability frameworks
• Experience as an early or sole ML hire at a startup
• Exposure to real-time fraud scoring systems or alternative payment rails like stablecoins

About the Company

Coinflow is a next-generation payment service provider revolutionizing global financial infrastructure with stablecoins, AI-driven fraud prevention, and instant settlement.