Senior Applied Economist, Causal Inference & Forecasting

Navan • New York City, NY

4d

About The Position

Navan is seeking a Senior Applied Economist to join the Data Science & 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. 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&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. What You’ll Do: Next-Generation Forecasting: 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. Causal Inference & Strategy: 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. Strategic Blueprinting: 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. Production-Level Data Science: 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. Internal Advisory: Act as the subject matter expert on economic literature and methodology, translating technical findings into strategic recommendations for executive leadership.

Requirements

• Education: An advanced degree (PhD preferred, Masters required) in Economics, Statistics, or a related quantitative field with a heavy emphasis on econometrics or causal inference.
• Experience: 4+ years of post-academic experience in an applied research, finance, or data science role, ideally within a high-growth tech environment or fintech.
• Technical Proficiency: Deep expertise in Python and its data science ecosystem (pandas, statsmodels, scikit-learn, etc.). Advanced SQL skills, with experience querying large-scale data warehouses like Snowflake . Experience working in production environments and a strong understanding of the ML lifecycle is nice to have.
• Econometric Mastery: Proven ability to apply advanced methods (e.g., Synthetic Control, IV, Diff-in-Diff, Structural Modeling) to messy, real-world datasets.
• Self-Starter Mentality: Experience functioning in "underdefined" spaces. As our first economist, you must be comfortable setting the roadmap.
• Communication: 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.

Nice To Haves

• Prior experience in Fintech, Payments, or Travel industries.
• Experience building and scaling "first-of-their-kind" functions within a data organization.

Responsibilities

• Next-Generation Forecasting: 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.
• Causal Inference & Strategy: 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.
• Strategic Blueprinting: 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.
• Production-Level Data Science: 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.
• Internal Advisory: Act as the subject matter expert on economic literature and methodology, translating technical findings into strategic recommendations for executive leadership.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior