Staff Data Scientist — Customer Success Analytics & AI

Intuit Inc.

San Diego (CA)

On-site

USD 194,000 - 263,000

Full time

4 days ago
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Job summary

Intuit Inc. is seeking a Staff Data Scientist to empower customer experiences across Services by delivering data-driven insights, experimentation, and predictive intelligence.

You will partner with CS, Product, Data Engineering, and Operations to drive engagement, retention, and long-term success for Payroll, Payments, and Bill Pay. This role focuses on measuring impact at scale, shaping measurement frameworks, and leveraging modern AI tooling to accelerate insights while preserving rigor and

Qualifications

  • 8+ years of data science, analytics, or product analytics with impact in CS, product, or GTM domains.
  • Deep foundation in causal inference and quasi-experimental design, beyond simple A/B testing.
  • Predictive modeling and segmentation used in production decisions.

Responsibilities

  • Serve as a strategic analytics partner to CS, Services, Product, and Operations leaders.
  • Design, implement, and interpret advanced experiments and causal analyses.
  • Develop scalable measurement frameworks for CS outcomes (engagement, retention, health).
  • Build predictive models and segmentation to improve targeting and prioritization.
  • Translate analyses into clear, actionable insights for senior leadership.

Skills

8+ years experience in data science
Strong communication
Storytelling
Cross-functional collaboration
Leadership

Education

Bachelor's degree in a quantitative field
Advanced degree preferred

Tools

SQL
Python
Pandas/Numpy
Scikit-learn
Statsmodels
A/B testing

Job description

Intuit Inc. is seeking a Staff Data Scientist to empower customer experiences across Services by delivering data-driven insights, experimentation, and predictive intelligence.

You will partner with CS, Product, Data Engineering, and Operations to drive engagement, retention, and long-term success for Payroll, Payments, and Bill Pay. This role focuses on measuring impact at scale, shaping measurement frameworks, and leveraging modern AI tooling to accelerate insights while preserving rigor and

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