Senior Risk ML Architect: Fraud & AML Leader

Global Payments; United States; On-site; USD 180,000 - 250,000; Full time

Job summary

Global Payments in the United States seeks a hands-on Lead Risk Data Scientist & ML Engineer to own the full lifecycle of fraud detection and risk models. You will lead end-to-end model development, deployment, and AI-assisted workflows, collaborating with Risk, Compliance, and Technology to scale solutions and ensure regulatory alignment.

This role combines deep technical leadership with pragmatic problem-solving in a fast-moving team, shaping detection strategies and governance across the

Qualifications

• 7+ years in data science, machine learning or MLOps.
• Experience deploying fraud/AML/credit risk models in production.
• Hands-on with AI-assisted workflows and agentic frameworks.
• Regulated financial services or fintech exposure preferred.
• Knowledge of SR 11-7 and model risk management.

Responsibilities

• Own end-to-end delivery of detection models and AI-assisted workflows.
• Drive model performance across lifecycle; production deployment.
• Translate regulatory requirements into detection strategies for risk operations.
• Lead cross-functional teams across Risk, Compliance, and Technology.
• Lead ML model development and AI workflow projects from conception to deployment.
• Mentor data scientists and engineers.
• Develop scalable data pipelines for model development and serving.
• Ensure models are explainable and auditable.

Skills

Data science

Machine learning

MLOps

Python

SQL

AWS SageMaker

Databricks

Snowflake

LLMs

Agentic workflows

Fraud risk

Regulatory knowledge

Tools

Git

GitHub Actions

CI/CD

Model monitoring

Infrastructure automation

Job description

Global Payments in the United States seeks a hands-on Lead Risk Data Scientist & ML Engineer to own the full lifecycle of fraud detection and risk models. You will lead end-to-end model development, deployment, and AI-assisted workflows, collaborating with Risk, Compliance, and Technology to scale solutions and ensure regulatory alignment.

This role combines deep technical leadership with pragmatic problem-solving in a fast-moving team, shaping detection strategies and governance across the