Lead Risk Data Scientist – ML Engineer

Global Payments Inc.

. Own the full lifecycle of fraud detection and risk models, including design, development, validation, deployment, serving, monitoring, and continuous refinement .

Posted 10/23/2026full-timeUnited StatesSenior💰 $150,300 - $201,400 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in fraud detection and risk modeling, including the design and deployment of AI-assisted workflows and scalable data pipelines. Proficient in regulatory compliance and model risk management within financial services, with a strong focus on collaboration and team mentorship.

Highest-signal resume keywords

Fraud Detection ModelsAI-Assisted WorkflowsPython ProficiencyMLOps ExperienceRegulatory Compliance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ScienceMachine LearningModel DevelopmentModel ValidationSQL ProficiencyGitCI/CD PracticesModel MonitoringDetection System DesignFraud Typologies

Soft Skills

Pragmatic Problem-SolverResourcefulVersatileCollaborativeMentoring

Tools & Technologies

AWS SageMakerDatabricksSnowflakeGitHub ActionsAWS GlueAWS LambdaAWS EventBridgeClaudeGPTLangChain

Industry Keywords

BSA/AML ComplianceFinCENSR 11-7Model Risk ManagementFinancial ServicesFintech

Tech Stack

Tools & technologies

AWSPythonSQL

About the role

Key responsibilities & impact

Own the full lifecycle of fraud detection and risk models, including design, development, validation, deployment, serving, monitoring, and continuous refinement
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
Guide agent-based systems that augment human decision-making in risk operations
Establish best practices for pilot-stage AI and agentic workflow deployments
Define and refine detection strategies based on emerging fraud patterns and regulatory requirements
Monitor precision, recall, false positives, and alert quality
Balance detection coverage, operational cost, and false-positive rates
Define governance standards for model development, validation, documentation, and change management
Ensure compliance with BSA/AML, OFAC, FinCEN, and SR 11-7 expectations
Partner with Model Risk Management and Compliance on validation and regulatory reviews
Serve as primary technical partner to Fraud Operations, Compliance, and Technology teams
Translate regulatory and operational requirements into technical execution plans
Lead cross-functional project teams from conception through deployment
Establish priorities, performance expectations, and delivery accountability
Mentor data scientists and engineers
Build team capabilities in detection modeling, data engineering, and AI/agentic systems

Requirements

What you’ll need

7+ years in data science, machine learning or MLOps
Proven experience developing, deploying, and maintaining fraud, AML, or credit risk detection models 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, including SR 11-7, and regulatory interactions
Strong proficiency in Python and SQL
MLOps experience with Git, GitHub Actions, CI/CD practices, model monitoring, retraining pipelines, and infrastructure automation
Hands-on experience with Databricks, Snowflake, and AWS SageMaker
AWS ecosystem expertise, including SageMaker, Glue, Lambda, EventBridge, and related services
Familiarity with foundational models such as Claude and GPT, and agent orchestration tools such as AWS AgentCore and LangChain
Understanding of fraud typologies, AML transaction monitoring methodologies, and detection system design
Resourceful and versatile, with the ability to work in a small, fast-moving team and deliver with constrained resources
Pragmatic problem-solver with a bias toward execution and measurable outcomes
Ability to guide project teams through ambiguous problems and drive clarity, structure, and delivery
Ability to collaborate across Risk, Compliance, and Technology functions
Must be legally authorized to work for any employer in the United States on a full-time basis without current or future immigration sponsorship

Benefits

Comp & perks

Medical, dental and vision care
EAP programs
Paid time off
Recognition programs
Retirement and investment options
Charitable gift matching programs
Worldwide days of service