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Staff Data Scientist, Intuit Customer Success

Intuit
Mountain View, CA Full Time
POSTED ON 2/27/2026
AVAILABLE BEFORE 4/27/2026

Come join the Intuit Customer Success data science team as a Staff Data Scientist to shape the strategy to enable best-in-class customer experiences for QuickBook customers.The Data Science team plays a critical role in shaping strategy, scaling new businesses, and delivering delightful customer experiences. Our mission is to accelerate decision-making through advanced models, insights, and experimentation that address our most important customer and business challenges.


Responsibilities

We are seeking a Staff Data Scientist to deliver impactful insights into business performance and growth opportunities, build predictive models and insights, and drive measurable outcomes. This role requires a strong background in quantitative analysis, data-driven decision-making, and expertise in working with large data sets.

  • Conceptualize business problems or opportunities, formulate hypotheses and goals, define key metrics, and make actionable recommendations.
  • Drive strategic insights that shape the future of Intuit's core Accounting offering, impacting millions of small businesses.
  • Develop predictive models, conduct experimentation beyond A/B testing, and generate actionable customer insights that inform product innovation.
  • Build and apply durable customer segmentation patterns to refine product targeting, positioning, and customer experience.
  • Partner closely with Product Management, Marketing, Engineering, Design, and Analytics leaders to deliver insights that drive product strategy and growth.
  • Translate complex data insights into actionable recommendations for technical and non-technical stakeholders and business leaders

Qualifications

The ideal candidate is a curious, proactive data scientist with experience in building scalable solutions, a strong understanding of customer behavior, and a passion for helping customers.

  • BS or MS degree in Statistics, Mathematics, Operations Research, Computer Science, Econometrics, or a related field.
  • 10 years of experience in data science or product analytics, with a strong foundation in predictive modeling, customer segmentation, and experimentation.
  • Ability to formulate data-backed strategies that will drive step-function growth for the business and increase customer benefit.
  • Ability to generate hypotheses grounded in customer behavior, industry trends, and external market factors.
  • Experience in designing and interpreting complex experiments beyond traditional A/B testing methods.
  • Demonstrated experience in building reusable and scalable analytics solutions, with a focus on efficiency and avoiding duplication of work.
  • Outstanding communication skills with the ability to influence decision-makers and build consensus with teams.
  • Quick learner, adaptable, with the ability to work independently or as part of a team in a fast-paced environment.

Technical Skills:

 

  • Advanced SQL skills and proficiency in visualization tools such as Qlik, Tableau, Plotly Dash.
  • Strong analytical and modeling skills using Python (for its rich suite of statistical and modeling libraries like NumPy, Pandas, Scikit-learn, etc.).
  • Experience with Causal inference techniques such as propensity score matching, difference-in-differences, and synthetic control methods.
  • Familiarity with Generative AI and other evolving technologies to accelerate insights from multi-modal data.

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: 



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