Global Payments
Lead Risk Data Scientist & ML Engineer
ALPHARETTA GEORGIA · 4d ago
Not specified7+ YOE
Quick summary
AI parsed- Experience
- 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; Python, SQL, MLOps (Git, GitHub Actions, CI/CD), Databricks, Snowflake, AWS SageMaker
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
- Design and deploy AI-assisted analyst workflows using LLMs and agentic frameworks; guide development of agent-based systems that augment human decision-making in risk operations
- Define and refine detection strategies based on emerging fraud patterns and regulatory requirements; maintain and monitor key performance metrics (precision, recall, false positives, alert quality)
- Lead cross-functional project teams through ML model and AI workflow development; provide technical guidance and mentorship to data scientists and engineers executing on risk initiatives
Full description
Job Description
Job Posting Description
Ready to take your career global?
Make your mark at one of the biggest names in payments. We are seeking a hands-on Lead Risk Data Scientist & ML Engineer to own the full lifecycle of fraud detection and risk models. This role combines deep data science expertise with practical AI/agentic workflow experience and the infrastructure knowledge needed to ship at scale.
What You’ll Own
In this role, you'll own the end-to-end delivery of detection models and AI-assisted workflows that power fraud, credit, and AML risk operations. You'll drive model pe…