Director - Transaction Fraud Analytics

Posted Monday, February 16, 2026 at 12:00 AM

Director of Transaction Fraud Analytics

Corpay is currently looking to hire a Director of Transaction Fraud Analytics within our Corporate Services – Credit & Risk division. This position falls under our Vehicle Payments LOB and is located in Brentwood, TN.

You will lead and grow high-impact analytics function responsible for reducing fraud losses while minimizing friction and protecting customer experience.

You will lead the transaction fraud analytics program across rules + models, performance measurement, and operational decisioning. The team is currently small but expected to grow. Over time, this role will own the fraud decision engine, including the operating model, governance, roadmap, and outcomes.

This position reports into the VP of Fraud Systems & Analytics and regularly collaborates with business leaders and the wider credit and risk teams.

As a Director of Transaction Fraud Analytics you will be expected to work in an office environment, with some flexible hybrid working. Corpay will set you up for success by providing:

• Assigned workspace in Brentwood, TN
• Formal, hands-on training

The responsibilities of the role will include:

• Owning transaction fraud analytics strategy and execution across rules and models, to drive measurable improvements in fraud loss, approval rate, and customer friction.
• Setting a clear roadmap for detection and decisioning capabilities, including prioritization, measurement, and delivery milestones.
• Establishing an operating cadence and governance for rule/model changes (testing, approvals, documentation, and post-deployment monitoring).
• Direct the development, tuning, and deployment of fraud rules and predictive models; drive continual improvement through champion/challenger and iterative optimization.
• Define and monitor core performance metrics including fraud rate, false positives, approval rate, detection latency, and lift.
• Build and maintain actionable executive dashboards and reporting, to clearly communicate risk posture, trends, and results.
• Serve as the primary analytics partner to Fraud Ops, Product, Engineering, Data, Compliance, and Customer teams to scale decisioning and improve customer experience.
• Translate emerging fraud patterns and operational signals into durable controls, automation, and platform enhancements.
• Drive alignment on tradeoffs (risk vs. friction) with clear, data-backed recommendations.
• Lead analytics response during major fraud events/incidents, including rapid analysis, containment actions, and executive updates.
• Own root-cause analysis and ensure postmortems result in lasting fixes (controls, monitoring, tooling, process, training).
• Lead a team of fraud analytics professionals; hire, coach, and develop talent as the function grows.
• Create clear role definitions, career development paths, and a culture of accountability and continuous improvement.

• 8+ years of experience in fraud analytics, payments risk, or transaction monitoring (issuer, fintech, processor, or network environments).
• 5+ years leading analytics teams and/or owning a fraud analytics program with measurable outcomes.
• Strong expertise in transaction fraud concepts: authorization decisioning, rules strategy, model performance, and fraud operations workflows.
• Advanced analytics fluency: strong SQL and data storytelling; ability to translate data into clear decisions for executives and partners.
• Demonstrated ability to partner across functions and drive execution through influence (Product/Engineering/Ops/Compliance).
• Comfortable operating in ambiguity and fast change—able to set direction while still driving results.
• Hands-on experience with modern analytics tooling (Tableau/Power BI, Python/R) and model development/monitoring (e.g., gradient boosting such as XGBoost/GBM, feature drift/PSI, A/B testing).
• Experience with real-time decisioning platforms and/or fraud engines (e.g., IBM Safer Payments, Falcon, Actimize, SAS, etc.).
• Familiarity with modern data stacks and streaming ecosystems (e.g., Snowflake/Databricks, Kafka, Spark).
• Strong understanding of governance and controls…