Staff Data Scientist, Customer Success — AI & Experiments

Intuit Inc.; Mountain View (CA); On-site; USD 194,000 - 263,000; Full time

Job summary

Intuit Inc. is seeking a Staff Data Scientist in Mountain View to serve as a senior analytics partner for Customer Success and Services.

You will shape measurement frameworks, lead advanced experimentation, and translate insights into strategic recommendations that drive engagement, retention, and revenue across payroll, payments, and bill-pay domains. You will build predictive models and segmentation, apply modern AI tools, and collaborate with data engineers to ensure data quality and scalable

Qualifications

• 8+ years in data science, analytics, or product analytics with impact in CS or GTM domains.
• Strong foundation in causal inference, quasi-experimental design, and experimentation beyond A/B testing.
• Experience building predictive models and segmentation used in production decisions.
• Proficient SQL and Python for analysis and experimentation.
• Comfort with AI tooling and AI/agent workflows to speed analytics while maintaining rigor.

Responsibilities

• Partner with CS, Services, Product, and Operations leaders to define problems and success metrics.
• Design and interpret experiments, including quasi-experiments and DSS methods to isolate impact.
• Develop scalable measurement frameworks for CS and Services outcomes (engagement, retention, health).
• Build predictive models and segmentation to improve targeting and prioritization.
• Translate analyses into actionable insights for senior leadership and cross-functional teams.

Skills

Advanced analytics

Causal inference

SQL

Python

Communication

Education

Bachelor's degree in quantitative field

Advanced degree preferred

Tools

SQL

Python

pandas

numpy

scikit-learn

statsmodels

Cursor

Claude

Job description

Intuit Inc. is seeking a Staff Data Scientist in Mountain View to serve as a senior analytics partner for Customer Success and Services.

You will shape measurement frameworks, lead advanced experimentation, and translate insights into strategic recommendations that drive engagement, retention, and revenue across payroll, payments, and bill-pay domains. You will build predictive models and segmentation, apply modern AI tools, and collaborate with data engineers to ensure data quality and scalable