Staff Data Scientist - Growth & Product Analytics

Intuit, Inc.; United States; On-site; USD 194,000 - 263,000; Full time

Job summary

Intuit, Inc. is seeking a Staff Data Scientist to accelerate growth through data-driven product-led strategies. You will partner with cross-functional teams to identify high-impact opportunities, design experiments, and translate insights into actionable hypotheses that boost customer value and revenue.

The role emphasizes causal inference, advanced analytics, and scalable data science practices, with a focus on instrumentation, data quality, and rapid iteration to drive product improvements.

Qualifications

• 5+ years of experience in data science or analytics.
• Proven proficiency in causal inference, statistical modeling, ML, and experimental design.
• Strong SQL, Python, and R skills with data visualization experience.

Responsibilities

• Set technical vision and data science roadmap for product funnel optimization.
• Apply causal inference and ML to turn data into actionable growth insights.
• Develop integrated customer journey views across business metrics.
• Design and analyze targeted experiments to validate hypotheses.
• Collaborate with Product, Engineering to translate insights into product enhancements.
• Improve instrumentation, data quality and logging for better analytics.
• Act as a technical SME and drive rigorous analytical practices.

Skills

Causal inference

Statistical modeling

Machine learning

Experimental design

SQL

Python

R

Data visualization

Cross-functional collaboration

Tools

Tableau

Power BI

Job description

Intuit, Inc. is seeking a Staff Data Scientist to accelerate growth through data-driven product-led strategies. You will partner with cross-functional teams to identify high-impact opportunities, design experiments, and translate insights into actionable hypotheses that boost customer value and revenue.

The role emphasizes causal inference, advanced analytics, and scalable data science practices, with a focus on instrumentation, data quality, and rapid iteration to drive product improvements.