Principal Data Scientist – Mailchimp Product

Company Overview

Job Overview

Mailchimp is a core pillar of Intuit’s SMB Ecosystem, enabling millions of small and mid-sized businesses to grow through marketing automation and customer intelligence. As we accelerate toward becoming an AI-driven platform, Product Data Science must evolve to operate at a new level of technical sophistication, scale, and strategic influence.

We are seeking a Principal Data Science Leader to partner with the leadership team and lead the AI transformation of the Mailchimp Product Data Science organization. This leader will modernize how data science is practiced by advancing modeling capabilities, experimentation rigor, generative AI adoption, and scalable decision systems while driving measurable revenue and growth outcomes.

This role requires a proven track record of building durable data science capabilities and production-grade solutions, not just delivering analyses. The ideal candidate will elevate the craft across the organization, establish higher technical standards, and position data science as a strategic force multiplier for product and growth.

Responsibilities

Strategic Leadership & Vision

• Define and lead the multi-year vision for Mailchimp Product Data Science, aligning AI, modeling, and experimentation investments with product strategy and measurable business outcomes.
  
  
• Partner with Data Science leadership to transform the function into an AI-native organization by modernizing tools, workflows, technical standards, and scalable decision systems.

Outcome-Driven Product Impact

• Own revenue and growth accountability for data science–driven initiatives, ensuring modeling, experimentation, and AI investments are directly tied to measurable business outcomes and prioritized for maximum impact.
  
  
• Lead the rapid development and deployment of predictive models, causal inference frameworks, and LLM-enabled solutions, leveraging modern AI tools to accelerate learning velocity and reduce time from insight to decision.
  
  
• Drive a high-speed experimentation culture, balancing rigor with agility, so teams continuously test, learn, and iterate, translating insights into scalable impact with clear post-launch accountability.

Capability Building & Craft Elevation

• Champion and scale durable Product Data Science capabilities by establishing rigorous standards across modeling, experimentation, model governance, and AI-enabled workflows while raising the technical bar through structured reviews, reusable frameworks, and clear quality benchmarks.
  
  
• Accelerate adoption of modern AI tools, LLMs, and automation to increase productivity, technical depth, and organizational leverage across the Data Science team.
  
  
• Mentor, develop, and retain top data science talent by fostering a culture of ownership, technical excellence, and continuous learning.

Qualifications

• 10+ years of experience in Product Data Science with a demonstrated track record of personally building, shipping, and scaling high-impact models and experimentation frameworks that drove measurable revenue and growth outcomes.
  
  

• Proven experience transforming data science practices, establishing modeling standards, experimentation rigor, reusable frameworks, and AI-native workflows across teams.
  
  

• Deep technical expertise in SQL and Python, with strong command of statistical modeling, causal inference, experimentation design, and machine learning at production scale.
  
  

• Hands-on experience applying LLMs and modern AI tooling to accelerate insight generation, modeling workflows, and decision velocity.
  
  

• Demonstrated ability to influence senior cross-functional leaders and drive strategic outcomes without direct authority.
  
  

• Strong mentorship track record, with evidence of elevating senior data scientists and raising the technical bar of an organization.

Preferred Qualifications

• Master’s degree or higher in Statistics, Computer Science, Economics, Applied Mathematics, Machine Learning, or a related quantitative field.
  
  

• Deep understanding of growth science, customer lifecycle value, segmentation, and personalization at scale.
  
  

• Experience productionizing AI-driven decision systems in complex product ecosystems.
  
  

• Familiarity with multi-product ecosystems and cross-sell and attach strategies within platform businesses.

Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is: