Global Risk ML Lead — Fraud, AML & AI Workflows

Worldpay; Atlanta (GA); On-site; USD 180,000 - 230,000; Full time

Job summary

Worldpay in the United States seeks a Lead Risk Data Scientist & ML Engineer to own end‑to‑end fraud, AML, and credit risk model development and deployment. You will drive performance, ensure explainability, and align with regulatory expectations while mentoring a small, high‑impact team.

You’ll design AI‑driven workflows, collaborate with Risk, Compliance, and Technology, and ship scalable data pipelines and production models that protect customers and the business.

Qualifications

• 7+ years in data science, machine learning or MLOps.
• Proven experience developing, deploying, and maintaining detection models (fraud, AML, or credit risk) in production environments.
• Hands‑on experience with AI‑assisted workflows, LLMs, and agentic frameworks (including pilot‑stage deployments).
• Experience in regulated financial services or fintech environments preferred.
• Exposure to model risk management frameworks (SR 11-7) and regulatory interactions.

Responsibilities

• Own the full lifecycle of ML models: design, development, validation, deployment, and serving in production.
• Lead model performance monitoring and continuous refinement using production data and investigation outcomes.
• Ensure models are explainable, auditable, and aligned with regulatory expectations.
• Design and oversee scalable batch and real‑time data pipelines supporting model development and serving.
• Design and deploy AI‑assisted analyst workflows using LLMs and agentic frameworks.
• Lead cross‑functional teams through ML model and AI workflow development from conception to deployment.

Skills

Python

SQL

MLOps

Databricks

Snowflake

AWS SageMaker

LLMs

Agentic frameworks

Git

GitHub Actions

Tools

CI/CD

Job description

Worldpay in the United States seeks a Lead Risk Data Scientist & ML Engineer to own end‑to‑end fraud, AML, and credit risk model development and deployment. You will drive performance, ensure explainability, and align with regulatory expectations while mentoring a small, high‑impact team.

You’ll design AI‑driven workflows, collaborate with Risk, Compliance, and Technology, and ship scalable data pipelines and production models that protect customers and the business.