TL;DR

Staff Data Scientist (Causal Inference): Leading the design and scaling of experimentation systems and causal inference methods for TurboTax and %hirify_global% with an accent on econometric rigor and AI-driven measurement frameworks. Focus on developing causal attribution for agentic AI, building scalable experimentation tooling, and driving high-impact scientific analyses.

Location: Mountain View, California; San Diego, California

Company

%hirify_global% is a global financial technology platform serving approximately 100 million customers worldwide with products like TurboTax, Credit Karma, QuickBooks, and Mailchimp.

What you will do

Lead innovation and scaling of experimentation best practices and systems across TurboTax.
Define and set the scientific standard for causal inference methods and mentor data scientists and economists.
Develop causal measurement frameworks for AI-driven systems and partner with product and AI teams.
Deliver high-impact scientific analyses to guide business decisions and shape the Decision Science roadmap.

Requirements

Location: Must be based in Mountain View or San Diego, California
Bachelor’s degree in Statistics, Economics, or related quantitative field; Master’s or PhD preferred.
5+ years of experience applying statistical and econometric methods in decision-making contexts.
Deep expertise in causal inference methods and experimentation system design.
Proficiency in SQL and Python or R.
Strong communication skills and executive presence.