Staff Data Scientist

Intuit is seeking a Staff Data Scientist for its GBSG Customer Success Data Science & Analytics team, based in Mountain View, CA (onsite). In this role, you will help shape how customer success and expert-services impact is measured at scale, partnering across Customer Success, Product, Data Engineering, and Operations to deliver analytics, experimentation, and predictive intelligence for Services businesses including Payroll, Payments, and Bill Pay.

The team’s mission is to enable world-class customer experiences across digital and expert-led channels through data-driven insights, experimentation, and predictive intelligence. You will play a key part in defining success metrics, building scalable measurement frameworks, and evaluating whether agentic and human-in-the-loop success motions improve real customer and business outcomes.

What you’ll do

• Act as a strategic analytics partner to Customer Success, Services, Product, and Operations leaders by defining problems, success metrics, and data-informed decision paths.
• Turn ambiguous business questions into clear hypotheses and rigorous analytical plans to evaluate Customer Success and expert-services programs, including CSM coverage and outbound and inbound-friction motions such as “Nail the Basics”.
• Design and run experiments beyond traditional A/B testing, using causal inference approaches (for example, quasi-experiments, DiD, matching, and synthetic control) to isolate incremental impact.
• Build and maintain scalable measurement frameworks for outcomes tied to engagement, retention, share-of-wallet, TPV growth, customer health, and support effectiveness.
• Develop predictive models and durable customer segmentation approaches to improve targeting, prioritization, and CSM assignment across the Services customer base.
• Identify and prioritize customer-friction and revenue-risk opportunities, and translate analysis into actionable roadmaps for Services leadership.
• Use modern AI tooling to accelerate analytics workflow while maintaining high standards for correctness and reproducibility (including LLM-assisted development environments such as Cursor and Claude, plus internal AI/MCP capabilities).
• Design and evaluate AI/ML- and LLM-powered customer experiences by establishing the measurement and causal frameworks that determine whether agentic and human-in-the-loop success motions drive outcomes.
• Communicate complex findings through clear narratives for technical and non-technical stakeholders, including senior leadership and cross-functional Services partners.
• Partner with Data Engineering to support data quality, well-defined metrics, and scalable analytics assets, especially during platform and data migrations.
• Promote analytics rigor, experimentation best practices, and reusable solutions that scale impact beyond individual projects.
• Collaborate across teams to role-model Intuit’s “Win Together” mindset and raise the analytical bar across the organization.

What you bring

• 8+ years in data science, analytics, or product analytics with demonstrated impact in customer success, product, or go-to-market domains.
• Deep expertise in advanced analytics, including causal inference and quasi-experimental design (DiD, matching, synthetic control, regression discontinuity), plus the ability to choose and defend the right method for ambiguous, real-world questions.
• Predictive modeling and segmentation experience with models (such as propensity, churn/retention, LTV, and customer health) used in production decisions.
• Advanced SQL and strong Python (pandas, numpy, scikit-learn, statsmodels) for analysis, modeling, and experimentation.
• Working fluency with modern AI tooling for data science, including LLM-based coding assistants (Cursor, Claude) and AI/agent workflows to increase speed and quality, with strong judgment on when human rigor must own the result.
• Proven ability to work with large, complex datasets and translate insights into business decisions.
• Strong communication and storytelling skills to influence senior stakeholders.
• Bachelor’s degree in a quantitative field (Statistics, Economics, Mathematics, Computer Science, Data Science, or related); advanced degree preferred.

Technologies you’ll use

• Cursor, Claude, SQL, Python, pandas, numpy, scikit-learn, statsmodels
• LLM-assisted development environments and internal AI/MCP capabilities
• AI/ML and LLMs, including agentic and human-in-the-loop success motions

Compensation

Salary range: USD 194,000 - 262,500 per year for the Mountain View location. Intuit provides a competitive compensation package with pay-for-performance rewards and may include a cash bonus and equity and benefits in line with applicable plans. Pay is based on job-related knowledge, skills, experience, and work location, and Intuit conducts regular comparisons across ethnicity and gender categories to support fair pay.