Streamline your corporate travel management and expense processes in one app. Save time, gain efficiency, and reduce costs with this powerful, all-in-one solution.
About the role
This role is ideal for a Fraud Strategy Decision Scientist who blends strong 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. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- 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)
More about this role
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 on machine learning features, rules development, and scalable fraud controls .
This role is ideal for a Fraud Strategy Decision Scientist who blends strong 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’s end-to-end fraud strategy , translating advanced analytics and ML outputs into actionable rules, thresholds, workflows, and policy decisions across expense card issuing, payments, onboarding, and travel fraud.
- Own and drive fraud strategy for key risk areas across travel and expense, balancing fraud loss reduction with customer experience.
- Design and evolve fraud rules, thresholds, and decision workflows , informed by data science models, ML features, and investigative...
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