Senior Applied Economist, Causal Inference & Forecasting at Navan

<p>Navan is seeking a <strong>Senior Applied Economist</strong> to join the Data Science &amp; Machine Learning team. This is a foundational, "first-of-its-kind" role at Navan, designed for a technical leader who can bridge the gaps between hands-on machine learning, rigorous economic theory, and driving business outcomes.</p> <p>In this role, you will be the primary architect of our internal economic "brain." You will move beyond point-estimate forecasting to build sophisticated models that account for market nuances, uncertainty, and causal drivers. You will partner closely with Finance, Treasury, and FP&amp;A to steer the company’s financial trajectory, while providing the strategic frameworks that Sales and Pricing teams use to maximize customer adoption and revenue.</p> <p><strong>What You’ll Do:</strong></p> <ul> <li style="font-weight: 400;"><strong>Next-Generation Forecasting:</strong> Uplevel our existing forecasting pipelines (currently built on Prophet). You will integrate econometric rigor to improve accuracy and, crucially, provide a range of likely outcomes (probabilistic forecasting) that Finance and Treasury can rely on for risk management.</li> <li style="font-weight: 400;"><span style="font-weight: 400;"><strong>Causal Inference &amp; Strategy:</strong> Design and execute experimental and quasi-experimental frameworks to identify the "levers" of the business. You will answer critical questions regarding price elasticity, product feature attribution, and the ROI of sales incentives.</span></li> <li style="font-weight: 400;"><span style="font-weight: 400;"><strong>Strategic Blueprinting:</strong> Partner with Sales and Account Management to create data-driven frameworks for pricing and customer retention. You will translate complex causal models into actionable blueprints for go-to-market teams.</span></li> <li style="font-weight: 400;"><span style="font-weight: 400;"><strong>Production-Level Data Science:</strong> Work hands-on within our ML infrastructure. You will write production-quality Python code to deploy models into our AWS and Snowflake-based ecosystem, ensuring your insights are automated and scalable.</span></li> <li style="font-weight: 400;"><span style="font-weight: 400;"><strong>Internal Advisory:</strong> Act as the subject matter expert on economic literature and methodology, translating technical findings into strategic recommendations for executive leadership.</span></li> </ul> <p><strong>What We’re Looking For:</strong></p> <ul> <li style="font-weight: 400;"><strong>Education:</strong> An advanced degree (PhD preferred, Masters required) in Economics, Statistics, or a related quantitative field with a heavy emphasis on econometrics or causal inference.</li> <li style="font-weight: 400;"><strong>Experience:</strong> 4+ years of post-academic experience in an applied research, finance, or data science role, ideally within a high-growth tech environment or fintech. <ul> <li><strong>Technical Proficiency:</strong> <ul> <li>Deep expertise in <strong>Python</strong> and its data science ecosystem (pandas, statsmodels, scikit-learn, etc.).</li> <li>Advanced <strong>SQL</strong> skills, with experience querying large-scale data warehouses like <strong>Snowflake</strong>.</li> <li>Experience working in&nbsp;<strong>production environments</strong> and a strong understanding of the ML lifecycle is nice to have.</li> </ul> </li> </ul> </li> <li><strong>Econometric Mastery:</strong> Proven ability to apply advanced methods (e.g., Synthetic Control, IV, Diff-in-Diff, Structural Modeling) to messy, real-world datasets.</li> <li><strong>Self-Starter Mentality:</strong> Experience functioning in "underdefined" spaces. As our first economist, you must be comfortable setting the roadmap.</li> <li><strong>Communication:</strong> The ability to explain not just the "what," but the "why" and the "what if." You can communicate uncertainty and risk to a CFO just as clearly as you can discuss model architecture with an ML Engineer.</li> <li><strong>Preferred Qualifications:</strong> <ul> <li>Prior experience in Fintech, Payments, or Travel industries.</li> <li>Experience building and scaling "first-of-their-kind" functions within a data organization.</li> </ul> </li> </ul><div class="content-pay-transparency"><div class="pay-input"><div class="description"><p>The posted pay range represents the&nbsp;anticipated&nbsp;low and high end of the compensation for this position and is subject to change based on business need. To determine a successful candidate’s starting pay, we carefully consider a variety of factors, including primary work location, an evaluation of the candidate’s skills and experience, market demands, and internal parity.<br><br>For roles with on-target-earnings (OTE), the pay range includes both base salary and target incentive compensation. Target incentive compensation for some roles may include a ramping draw period. Compensation is higher for those who exceed targets. Candidates may receive more information from the recruiter.</p></div><div class="title">Pay Range</div><div class="pay-range"><span>$121,500</span><span class="divider">&mdash;</span><span>$270,000 USD</span></div></div></div>