Fraud Strategy Decision Scientist at Navan

<p>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&nbsp;<strong>Fraud Strategy Decision Scientist</strong>&nbsp;to lead data-driven fraud strategy initiatives focused on <strong>machine learning features, rules development, and scalable fraud controls</strong>.</p> <p>This role is ideal for a <strong>Fraud Strategy Decision Scientist</strong> who blends <strong>strong data science intuition with practical fraud rule design</strong>, 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.</p> <p>You will play a critical role in shaping Navan’s <strong>end-to-end fraud strategy</strong>, translating advanced analytics and ML outputs into <strong>actionable rules, thresholds, workflows, and policy decisions</strong> across expense card issuing, payments, onboarding, and travel fraud.</p> <p><strong>What You’ll Do</strong></p> <ul> <li>Own and drive <strong>fraud strategy</strong> for key risk areas across travel and expense, balancing fraud loss reduction with customer experience.</li> <li>Design and evolve <strong>fraud rules, thresholds, and decision workflows</strong>, informed by data science models, ML features, and investigative insights.</li> <li>Partner closely with Data Science teams to translate <strong>machine learning model outputs and features</strong> into effective, explainable fraud strategies.</li> <li>Lead strategy development across onboarding, payments, expense submissions, and transaction monitoring.</li> <li>Apply advanced analytics techniques (trend analysis, segmentation, clustering, network analysis) to identify emerging fraud patterns and control gaps.</li> <li>Perform <strong>root-cause analysis and loss attribution</strong>, quantifying financial impact and prioritizing strategy improvements.</li> <li>Own strategy performance metrics, including fraud loss, approval rates, false positives, and customer friction.</li> <li>Collaborate cross-functionally with <strong>Fraud Operations</strong> to ensure strategies are operationally executable and continuously optimized.</li> <li>Partner with <strong>Engineering and Product</strong> to implement fraud strategies into real-time and batch decisioning systems.</li> <li>Drive experimentation and A/B testing of rules, thresholds, and model-driven strategies.</li> <li>Contribute to the long-term <strong>fraud strategy roadmap</strong>, including tooling, rule engines, model integration, and automation.</li> <li>Support vendor evaluations and third-party data integrations to enhance detection signals.</li> <li>Mentor junior fraud strategists and analysts, setting best practices for strategy design, documentation, and governance.</li> </ul> <p><strong>What We’re Looking For</strong></p> <ul> <li><strong>7–10+ years</strong> of experience in fraud strategy, fraud analytics, or financial crime risk management.</li> <li>Strong experience designing and managing <strong>fraud rules, policies, and decision strategies</strong> in production environments.</li> <li>Deep understanding of how <strong>machine learning models and features</strong> are used to inform fraud decisions.</li> <li>Proficiency in <strong>SQL</strong> and strong working knowledge of <strong>Python</strong> for analysis and strategy validation.</li> <li>Experience working with large-scale data platforms such as <strong>Snowflake, Databricks, Spark</strong>, or similar.</li> <li>Solid understanding of <strong>card payments, transaction flows, identity verification</strong>, and fraud typologies (ATO, synthetic identity, first-party fraud, third-party fraud, scams).</li> <li>Demonstrated ability to partner effectively with <strong>Data Science, Engineering, Product, and Fraud Operations</strong> teams.</li> <li>Strong analytical mindset with the ability to translate complex data into clear, actionable strategy decisions.</li> <li>Excellent communication skills, including presenting strategy recommendations to senior leadership.</li> <li>Experience in fintech, payments, travel, or e-commerce environments preferred.</li> <li>Bachelor’s degree in a quantitative or analytical field; Master’s degree preferred.</li> </ul><div class="content-conclusion"><p>&nbsp;</p> <p>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.&nbsp;</p> <p><strong>Human oversight:</strong>&nbsp;<span style="color: #000000; font-family: Arial, sans-serif;">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.&nbsp;</span></p> <ul> <li> <p><strong>Your rights: </strong>If you prefer to have your application reviewed without AI assistance, you may request a human evaluation by entering your email <a href="https://my.metaview.app/applications/opt-out?organization=15dd7e883f">here</a>. Your decision to do so will not affect how your candidacy is evaluated.&nbsp;</p> </li> </ul> <p>Please refer to our<a href="https://navan.com/candidate-privacy-notice"> Candidate Privacy Notice</a> for more information about our processing of personal data, and your rights.</p></div>