Principal Data Scientist Lead

About the role

Vision & Standards: You set the long-term vision and standards for experimentation, causal inference, and machine learning across the organization. High-Stakes Analysis: You drive the most complex, high-stakes analyses where correct causal identification is critical to strategic decisions. Frameworks: You architect scalable modeling and experimentation frameworks adopted across teams.

Executive Advisory: You advise executives and cross-functional leaders on measurement strategy and interpretation of results. Mentorship: You mentor senior data scientists and shape hiring and technical growth for the discipline. Excellence: You champion methodological excellence, reproducibility, and compelling data storytelling.

Bachelor's Degree in Computer Science, Information Technology (IT), or related field AND 10+ years technical support, technical consulting experience, or information technology experience These requirements include but are not limited to the following specialized security screenings: Citizenship & Citizenship Verification: This position requires verification of U.S. citizenship due to citizenship-based legal restrictions.

Specifically, this position supports United States federal, state, and/or local United States government agency customer and is subject to certain citizenship-based restrictions where required or permitted by applicable law. To meet this legal requirement, citizenship will be verified via a valid passport.

Bachelor's Degree in Computer Science, Information Technology, or related field AND 15+ years of technical support, technical consulting experience, or information technology experience OR equivalent experience. Authority in causal inference — able to design novel identification strategies and adjudicate hard causal questions. Deep statistical mastery — inference, uncertainty, experimental design, and modern statistical methods.

Expert ML skills — advanced modeling, validation, and production-grade deployment at scale. Deep experience evaluating LLMs and/or AI agents — defining evaluation strategy, novel benchmarks, and measurement standards for model and agent quality, safety, and reliability.

Data storytelling — setting the bar for communicating insight through compelling data stories and enhanced visualizations in Python (e.g., matplotlib, seaborn, plotly) or other tools. Demonstrated influence on company strategy through causal and statistical work. Deep experience with causal ML tooling and large-scale experimentation platforms. Expert proficiency in Python or R and SQL.