Staff GTM Data Scientist - Remote

About the Role

We are seeking a Staff GTM Data Scientist to join our team at PandaDoc. In this remote position, you will serve as a senior analytical leader, embedding yourself deeply in our product and business data to uncover non-obvious insights and drive actionable recommendations. A primary focus of this strategic role is to champion and drive the organizational shift toward a data-driven culture.

What You'll Do

• Lead the Experimentation Roadmap: Define, champion, and execute a strategic roadmap for measuring impact across PandaDoc, focusing on high-leverage business questions related to customer workflows, churn risk, and long-term value (LTV).
• Advanced Experiment Design: Design, implement, and rigorously analyze complex A/B tests, multivariate experiments, and adaptive experimentation methods, including the application of Bayesian experimentation.
• Apply advanced causal inference techniques to scenarios where randomized controlled trials (RCTs) are infeasible.
• Conduct complex, proactive, and exploratory analysis to discover latent user behavior, emerging trends, and root causes of changes in key metrics.
• Define, instrument, and govern a unified Key Performance Indicator (KPI) framework that maps low-level product health metrics to high-level business outcomes.
• Partner with Data Engineering to design and build scalable, self-serve experimentation tooling and reusable analytical assets.
• Act as a strategic thinker by translating complex statistical findings into clear, compelling, and actionable business narratives for cross-functional partners.
• Serve as a technical subject matter expert, training and mentoring junior and mid-level data scientists.

Requirements

• 6+ years of professional experience in an applied data science, economics, or product analytics role.
• B.A. or B.S. in Mathematics, Statistics, Economics, Computer Science, or a related quantitative discipline.
• Demonstrated expertise in applying a wide range of Causal Inference methods.
• Expertise in advanced statistical methodologies for A/B testing.
• Mastery of advanced statistical modeling, time-series analysis, and quantitative methods.
• Advanced proficiency in Python or R for statistical modeling.
• Expert-level proficiency in SQL and experience working with established data warehouses.
• Experience with data transformation and workflow management tools such as dbt, Airflow, or Databricks is a strong plus.

Nice to Have

• Experience in a SaaS domain and a strong focus on Product Data Science.

What We Offer

• Annual base salary of up to $190,000-$210,000.
• Competitive salary with health and commuter benefits.
• Company paid life & disability insurance.
• 20+ PTO days.
• 401K and FSA plans.
• A fun team of Pandas to work with!