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Senior Applied Economist, Causal Inference & Forecasting

Navan
New York, NYApr 9, 2026·Posted 2 days ago
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Domain

Tech Stack

PythonSQLSnowflakeAWSProphetpandasstatsmodelsscikit-learn

Must-Have Requirements

  • Advanced degree (Masters minimum, PhD preferred) in Economics, Statistics, or related quantitative field with econometrics/causal inference emphasis
  • 4+ years post-academic experience in applied research, finance, or data science role
  • Deep expertise in Python and data science ecosystem (pandas, statsmodels, scikit-learn)
  • Advanced SQL skills with large-scale data warehouse experience (Snowflake)
  • Proven ability to apply advanced econometric methods (Synthetic Control, IV, Diff-in-Diff, Structural Modeling)
  • Self-starter mentality comfortable operating in underdefined spaces
  • Ability to communicate uncertainty and risk to executive leadership

Nice to Have

  • -Experience working in production environments
  • -Strong understanding of ML lifecycle
  • -Prior experience in Fintech, Payments, or Travel industries
  • -Experience building and scaling first-of-their-kind functions

Description

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.

What We’re Looking For

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.

Preferred Qualifications

Prior experience in Fintech, Payments, or Travel industries. Experience building and scaling "first-of-their-kind" functions within a data organization. The posted pay range represents the anticipated 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. 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. Pay Range $121,500 —

$270,000 USD