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Navan is expanding its Fraud Risk Management organization and seeking a Fraud Strategy Decision Scientist to lead data-driven fraud strategy initiatives. This role bridges advanced analytics, machine learning, and practical fraud rule design to reduce fraud losses while enabling business growth across Navan's travel and expense platforms.
You will own fraud strategy for key risk areas across travel and expense, balancing fraud loss reduction with customer experience. Key responsibilities include:
- Design and evolve fraud rules, thresholds, and decision workflows informed by data science models, ML features, and investigative insights
- Partner closely with Data Science teams to translate machine 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
- Perform root-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 with Fraud Operations to ensure strategies are operationally executable and continuously optimized
- Partner with Engineering 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-term fraud 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
Navan is a Nasdaq-listed AI-powered business travel and expense platform. The company has been recognized as a Best Place to Work by Built In (2023–2026), a G2 Best Global Software Company (2025–2026), Forbes Cloud 100 (2022–2025), and CNBC Disruptor 50 (2022–2025). Employees work from the office four days a week. Benefits include healthcare coverage, retirement savings programs, equity participation, flexible time off, paid parental leave, mental health resources, and travel-related perks.
REQUIREMENTS:
- 7–10+ years of experience in fraud strategy, fraud analytics, or financial crime risk management
- Strong experience designing and managing fraud rules, policies, and decision strategies in production environments
- Deep understanding of how machine learning models and features are used to inform fraud decisions
- Proficiency in SQL and strong working knowledge of Python for analysis and strategy validation
- Experience working with large-scale data platforms such as Snowflake, Databricks, Spark, or similar
- Solid understanding of card payments, transaction flows, identity verification, and fraud typologies (ATO, synthetic identity, first-party fraud, third-party fraud, scams)
- Demonstrated ability to partner effectively with Data 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
