Fraud Strategy Decision Scientist

Navan is expanding its Fraud Risk Management organization to build world-class fraud prevention and detection capabilities across our travel and expense platforms. We are seeking a Fraud Strategy Decision Scientist to lead data-driven fraud strategy initiatives focused onmachine learning features, rules development, and scalable fraud controls.

This role is ideal for aFraud Strategy Decision Scientist who blendsstrong data science intuition with practical fraud rule design, understands how models and rules work together in production, and can partner deeply with Product, Engineering, and Fraud Operations to reduce fraud losses while enabling business growth.

You will play a critical role in shaping Navan’send-to-end fraud strategy, translating advanced analytics and ML outputs intoactionable rules, thresholds, workflows, and policy decisions across expense card issuing, payments, onboarding, and travel fraud.

What You’ll Do

• Own and drivefraud strategy for key risk areas across travel and expense, balancing fraud loss reduction with customer experience.
• Design and evolvefraud rules, thresholds, and decision workflows, informed by data science models, ML features, and investigative insights.
• Partner closely with Data Science teams to translatemachine learning model outputs and features into effective, explainable fraud strategies.
• Lead strategy development across onboarding, payments, expense submissions, and transaction monitoring.
• Apply advanced analytics techniques (trend analysis, segmentation, clustering, network analysis) to identify emerging fraud patterns and control gaps.
• Performroot-cause analysis and loss attribution, quantifying financial impact and prioritizing strategy improvements.
• Own strategy performance metrics, including fraud loss, approval rates, false positives, and customer friction.
• Collaborate cross-functionally withFraud Operations to ensure strategies are operationally executable and continuously optimized.
• Partner withEngineering and Product to implement fraud strategies into real-time and batch decisioning systems.
• Drive experimentation and A/B testing of rules, thresholds, and model-driven strategies.
• Contribute to the long-termfraud strategy roadmap, including tooling, rule engines, model integration, and automation.
• Support vendor evaluations and third-party data integrations to enhance detection signals.
• Mentor junior fraud strategists and analysts, setting best practices for strategy design, documentation, and governance.

What We’re Looking For

• 7–10+ years of experience in fraud strategy, fraud analytics, or financial crime risk management.
• Strong experience designing and managingfraud rules, policies, and decision strategies in production environments.
• Deep understanding of howmachine learning models and features are used to inform fraud decisions.
• Proficiency inSQL and strong working knowledge ofPython for analysis and strategy validation.
• Experience working with large-scale data platforms such asSnowflake, Databricks, Spark, or similar.
• Solid understanding ofcard payments, transaction flows, identity verification, and fraud typologies (ATO, synthetic identity, first-party fraud, third-party fraud, scams).
• Demonstrated ability to partner effectively withData Science, Engineering, Product, and Fraud Operations teams.
• Strong analytical mindset with the ability to translate complex data into clear, actionable strategy decisions.
• Excellent communication skills, including presenting strategy recommendations to senior leadership.
• Experience in fintech, payments, travel, or e-commerce environments preferred.
• Bachelor’s degree in a quantitative or analytical field; Master’s degree preferred.

Navan uses AI-assisted Automated Employment Decision Tool (Metaview) to assist with evaluating resumes against job qualifications for this role. All final decisions are made by human recruiters and hiring managers. 

Human oversight: Metaview does not automatically reject candidates or make final hiring decisions. Our recruiters and hiring managers review all outputs and make the final hiring decision regarding every application. 

• Your rights:If you prefer to have your application reviewed without AI assistance, you may request a human evaluation by entering your emailhere. Your decision to do so will not affect how your candidacy is evaluated. 

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