Senior Data Analyst, Fraud Investigations

Navan is building out a best-in-class fraud risk management team to support our rapidly growing travel and expense management businesses. We are seeking a Senior Data Analyst, Fraud Investigations with strong analytical and investigative skills to help identify, analyze, and disrupt emerging fraud patterns. This role requires a data-driven problem solver with deep expertise in SQL, Snowflake, and advanced analytics techniques such as cluster analysis to detect organized fraud rings and take swift, decisive action. The position will report to the Head of Fraud Operations, Investigations, and Threat Intelligence within the Risk Management organization.

What You’ll Do:

• Leverage advanced SQL and Snowflake expertise to extract, analyze, and interpret large, complex datasets to detect unusual patterns and potential fraud activity.
• Conduct cluster and network analysis to identify organized fraud rings, coordinated activity, and high-risk behaviors across Navan’s platforms.
• Lead end-to-end investigations of sophisticated fraud cases, collaborating closely with Fraud Operations, Product, and Security teams.
• Translate analytical findings into actionable strategies to mitigate losses and strengthen fraud detection frameworks.
• Develop and maintain dashboards, reports, and fraud indicators that surface emerging risks in near real-time.
• Partner with engineers and data scientists to enhance existing rules, models, and anomaly detection systems.
• Present findings and recommendations to senior leadership in a clear, concise, and actionable manner.
• Continuously improve investigative methodologies, data tools, and internal processes to enhance fraud detection and response capabilities.

What We’re Looking For:

• Bachelor’s degree in Data Science, Computer Science, Statistics, Business Analytics, or a related field (Master’s preferred).
• 2–5 years of professional experience in fraud analytics, fraud investigations, or financial crime risk management.
• Expert-level proficiency in SQL and strong hands-on experience with Snowflake or equivalent data warehouse technologies.
• Proven experience applying cluster analysis, network analysis, or anomaly detection to identify coordinated fraud activity.
• Strong analytical mindset with the ability to connect seemingly unrelated data points into coherent fraud hypotheses.
• Exceptional attention to detail, critical thinking, and investigative intuition.
• Strong communication skills and able to translate complex analytical findings into clear business insights.
• Experience in travel, fintech, or e-commerce industries is a plus.