Sr Staff Data Scientist, Customer Success

Company Overview

Job Overview

The GBSG Customer Success Data Science & Analytics team partners with leaders across Customer Success, Product, Operations, and Engineering to enable exceptional customer experiences and durable business growth through data-driven insights, experimentation, and predictive intelligence.

As a Senior Staff Data Scientist, you will operate as a senior individual contributor and strategic thought partner, tackling ambiguous, high-impact problems that span customer engagement, retention, experience quality, and operational effectiveness. You will shape how Customer Success impact is measured at scale, lead advanced analytical and experimentation efforts, and influence strategy through rigorous insights and compelling data storytelling.

This role is intentionally broad in scope and offers the opportunity to help define where and how data science can most effectively drive Customer Success outcomes as GBSG evolves its platforms, operating models, and AI-enabled experiences.

Responsibilities

• Serve as a strategic analytics partner to Customer Success, Product, and Operations leaders, helping frame problems, define success metrics, and guide data-informed decision-making.
  
  
• Tackle ambiguous business questions by formulating hypotheses, designing analytical approaches, and synthesizing insights that inform strategy and execution.
  
  
• Design, execute, and interpret advanced experiments and causal analyses beyond traditional A/B testing (e.g., quasi-experiments, difference-in-differences, matching, synthetic control).
  
  
• Develop and evolve scalable measurement frameworks for key Customer Success outcomes such as engagement, retention, customer health, satisfaction, and support effectiveness.
  
  
• Build predictive models and segmentation frameworks that improve targeting, prioritization, and personalization across customer success motions.
  
  
• Translate complex analyses into clear, actionable narratives for both technical and non-technical audiences, including senior leadership.
  
  
• Partner closely with Data Engineering and platform teams to ensure data quality, metric consistency, and reusable analytics assets, especially in the context of evolving data architectures.
  
  
• Evaluate and help measure the impact of AI- and ML-driven customer experiences, including human-assisted and digital channels.
  
  
• Champion analytics rigor, experimentation best practices, and reusable solutions that scale impact beyond individual projects.
  
  
• Mentor and influence other data scientists by raising the bar on analytical quality, technical depth, and business impact.
  
• Role-model Intuit’s Win Together mindset through deep cross-functional collaboration and boundaryless problem-solving.

Qualifications

• 7+ years of experience in data science, analytics, or applied research, with demonstrated impact in customer success, product, go-to-market, or adjacent domains.
  
  Strong foundation in statistics, experimentation, and causal inference, including experience designing analyses beyond simple A/B tests.
  
  
• Advanced proficiency in SQL and Python for data analysis, modeling, and experimentation (e.g., pandas, numpy, scikit-learn, statsmodels).
  
  
• Proven ability to work with large, complex datasets and turn insights into concrete business decisions.
  
  
• Experience building scalable, reusable analytics or modeling solutions that improve consistency and efficiency.
  
  

• Strong communication and data storytelling skills, with a track record of influencing cross-functional stakeholders.
  
  

• Bachelor’s degree in a quantitative field (e.g., Statistics, Economics, Mathematics, Computer Science, Data Science, or related); advanced degree preferred.
  

Preferred

• Experience in SaaS, fintech, platform, or SMB-focused products.
  
  

• Familiarity with Customer Success concepts and metrics (e.g., lifecycle engagement, churn risk, customer health, support effectiveness).
  
  

• Experience partnering closely with Product, Engineering, and AI/ML teams.
  
  

• Familiarity with BI and visualization tools (e.g., Tableau, Qlik, QuickSight).
  
  

• Experience using version control (git) and applying software engineering best practices to analytics workflows.
  
  

• Exposure to Generative AI or LLM-powered analytics or customer-facing use cases.

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:

Bay Area California $ 204,500- 276,500

Southern California $ 197,500- 267,500