Sr. Staff Data Scientist

Intuit; Mountain View (CA); On-site; USD 211,000 - 285,000; Full time

Benefits offered by this job

Cash bonus

Equity rewards

Job summary

Intuit is hiring a Senior Staff Data Scientist for the GBSG Product Growth team in Mountain View. You will lead data-driven experiments, surface growth opportunities, and translate insights into product improvements across the customer journey.

The role emphasizes causal inference, advanced analytics, and scalable experimentation, partnering with Product, Engineering, and Design to accelerate growth and customer outcomes.

Qualifications

• 8+ years of experience in data science or analytics.
• Proficiency in causal inference, statistical modeling, machine learning, and experimental design.
• Advanced skills in SQL, Python, R; able to communicate insights with Tableau or Power BI.
• Experience with data integration and pipeline development is a plus.
• Strong ability to quickly understand new business areas and master essential data and metrics for decision-making.
• Excellent communication and storytelling skills to influence stakeholders with data-driven insights.
• Customer-centric mindset with empathy and a bias towards improving customer experiences.

Responsibilities

• Contribute to and refine a data science roadmap focused on product funnel optimization and scalable growth initiatives.
• Use causal inference, advanced statistical modeling, and ML techniques to turn data into actionable insights.
• Build an integrated view of the customer journey across key business metrics.
• Design, implement, and analyze targeted experiments to validate hypotheses with data-driven insights.
• Collaborate with cross-functional partners to translate insights into strategic product enhancements.
• Support improvements in instrumentation, data quality, and logging for better understanding of customer behavior.
• Act as a technical leader within the Product Growth team by promoting analytical rigor and innovative problem-solving.
• Mentor and share best practices in causal inference and analytics to strengthen the growth framework.
• Rapidly assimilate diverse metrics and data sources to uncover insights and high-impact hypotheses.
• Balance rigorous analysis with fast, iterative execution so insights translate into strategies.

Skills

Data science experience

Causal inference

SQL

Python

R

Tableau

Power BI

Experimental design

Communication

Customer-centric mindset

Tools

SQL

Python

R

Tableau

Power BI

Job description

Intuit is hiring a Senior Staff Data Scientist to help accelerate product growth through experimentation and deep analytics on the GBSG Product Growth team. This role is built around a data-driven, product-led approach, combining scalable growth loops, rigorous experimentation, and cross-functional collaboration to find the highest-impact opportunities across the product ecosystem.

As a senior individual contributor, you will partner with Product, Engineering, Design, and other teams to surface actionable insights and translate them into hypotheses that improve both customer outcomes and business performance. You will also champion analytical rigor and causal inference, while moving quickly from analysis to iterative execution.

What you’ll do

• Contribute to and refine a data science roadmap focused on product funnel optimization and scalable growth initiatives.
• Use causal inference, advanced statistical modeling, and machine learning techniques to turn complex data into actionable insights.
• Build an integrated view of the customer journey across key business metrics, learning new areas quickly to identify growth opportunities.
• Design, implement, and analyze targeted experiments to validate hypotheses with data-driven insights and sound causal analysis.
• Collaborate with cross-functional partners to translate insights into strategic product enhancements.
• Support ongoing improvements in instrumentation, data quality, and logging to strengthen analytical capabilities and understanding of customer behavior.
• Act as a technical leader within the Product Growth team by championing analytical rigor and innovative problem-solving.
• Mentor and share best practices in causal inference and advanced analytics to strengthen the team’s overall growth framework.
• Rapidly assimilate diverse metrics and data sources to uncover insights and propose high-impact hypotheses.
• Balance rigorous analysis with fast, iterative execution so insights move quickly into effective strategies.

What you bring

• 8+ years of experience in data science or analytics, with a proven record of using advanced analytical methods to drive product and business growth.
• Demonstrated proficiency in causal inference, statistical modeling, machine learning, and experimental design.
• Advanced skills in SQL, Python, R, plus experience using data visualization tools such as Tableau or Power BI to communicate insights.
• Experience with data integration and pipeline development is a plus.
• Strong ability to quickly understand new business areas and master essential data and metrics for decision-making.
• Excellent communication and storytelling skills, with a track record of influencing technical and non-technical stakeholders through data-driven insights.
• A customer-centric mindset with empathy and a commitment to uncover opportunities that improve customer experiences.
• An agile, entrepreneurial approach that balances long-term strategic work with rapid experimentation.

Tools you’ll use

SQL, Python, R, Tableau, Power BI

Compensation and benefits

• This position may be eligible for a cash bonus.
• Equity rewards and benefits may be offered in line with applicable plans and programs.
• Pay is based on job-related knowledge, skills, experience, and work location.
• Intuit conducts regular comparisons across categories of ethnicity and gender for pay fairness.
• Expected base pay range for Mountain View: USD 210,500 - 284,500 per year.

Location: Mountain View, CA (onsite)

Team focus: Global Business Solutions Group (GBSG) Product Growth, accelerating business outcomes using a data-driven, product-led approach.