Senior Data Scientist, Fraud Operations

Navan is expanding its Fraud Risk Management team to build world-class fraud detection, prevention, and analytics capabilities supporting our rapidly growing travel and expense businesses. We are seeking a highly skilled and visionary Data Scientist, Fraud, to design and scale advanced data science solutions that protect Navan’s customers, platform, and financial ecosystem.

This is a strategic and hands-on role, where you’ll partner with other fraud strategy members, product, engineering, and data teams to design the ML features, build the rule workflow, build next-generation fraud models, develop actionable insights, and lead the application of AI/ML to mitigate emerging fraud threats both in expense card issuing and travel fraud. The ideal candidate combines deep technical expertise in machine learning and data systems with a strong understanding of payment, identity, and transactional fraud patterns.

Location: Bangalore, India

What You’ll Do

• Lead the design and deployment of advanced ML features, build rule workflows to detect and prevent fraud across travel and expense.

• Lead the design and development of advanced ML and statistical models to detect, predict, and prevent fraudulent behavior across onboarding, payments, and expense workflows.

• Drive applied research in anomaly detection, network/graph modelling, real-time clustering, and link analysis to identify emerging fraud patterns and organized fraud rings.

• Partner cross-functionally with other Risk Strategy team members, Fraud operations, Engineering, and Product teams to translate insights into scalable prevention rules, thresholds, and model-driven interventions.

• Own model lifecycle management from feature engineering and experimentation to monitoring, model retraining, and post-deployment optimisation.

• Perform root-cause and loss attribution analyses, identifying vulnerabilities and quantifying financial impact to inform control effectiveness and business risk appetite.

• Sign up for the stretch fraud loss goals and the ability to drive the roadmap to meet the goal.

• Collaborate with Data Engineering and Platform teams to define data schemas, pipelines, and infrastructure that enable real-time fraud monitoring and analytics.

• Mentor junior data scientists and fraud analysts, providing technical guidance and driving excellence in experimentation, model governance, and reproducibility.

• Contribute to the overall fraud strategy roadmap, helping evolve Navan’s machine learning and analytics capabilities to stay ahead of emerging fraud trends.

• Partner with external vendors and third-party data sources to enrich detection signals and improve model precision and recall.