Senior Data Scientist

Category Data

Location
San Diego, California; Mountain View, California
Job ID 21732

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Company Overview

Intuit is the global financial technology platform that powers prosperity for the people and communities we serve. With approximately 100 million customers worldwide using products such as TurboTax, Credit Karma, QuickBooks, and Mailchimp, we believe that everyone should have the opportunity to prosper. We never stop working to find new, innovative ways to make that possible.

Job Overview

We are seeking a Senior Data Scientist to join the Intuit Customer Success (ICS) Data Science & Analytics team supporting Expert Experiences and Intuit Academy. This role focuses on delivering high-quality, decision-ready analytics and data science models that inform training effectiveness, expert readiness, and customer success outcomes.

You will collaborate closely with cross-functional partners across Product, Learning & Development, Quality, Operations, and Analytics to translate ambiguous business questions into clear analytical problems, design reusable analytical frameworks, and develop scalable insights and recommendations. The ideal candidate brings strong analytical judgment, rigor, and the ability to operate independently in complex problem spaces.

Collaborating closely with the Intuit Assist Expert Experiences team, your contributions will be instrumental in shaping the future of customer success at Intuit as we build a service platform to empower our customers beyond core product use.

Responsibilities

Key Responsibilities

Data Science & Analytical Problem Solving

• Translate ambiguous business questions into well-defined analytical hypotheses, causal frameworks, and measurable outcomes.
• Own the end-to-end data science lifecycle, including data acquisition, exploration, validation, feature engineering, statistical modeling, causal inference, and results interpretation.
• Apply advanced statistical and machine learning techniques to uncover drivers of performance, behavior, and outcomes.
• Ensure analytical outputs are statistically sound, reproducible, and decision-ready.

Experimentation, Causal Inference & Measurement

• Design, implement, and analyze experiments (e.g., A/B tests, quasi-experiments, pilots) to estimate the causal impact of interventions.
• Apply causal inference methods (e.g., matching, regression, difference-in-differences) to address confounding, bias, and incomplete data.
• Establish measurement frameworks that balance rigor with practical constraints in real-world data environments.

Data Interpretation & Insight Communication

• Synthesize complex analytical results into clear, actionable insights that influence strategy and product or program decisions.
• Communicate findings through compelling data narratives and visualizations tailored to technical and non-technical stakeholders.
• Collaborate cross-functionally to align on assumptions, metrics definitions, and interpretation of results.

Scalable & Reproducible Analytics

• Develop standardized metrics, analytical frameworks, and reusable data science assets.
• Contribute to scalable dashboards and reporting pipelines that support ongoing measurement and experimentation.

••Partner with Data Engineering and Analytics teams to ensure data reliability, consistency, and analytical best practices.

Qualifications

Qualifications

• 4+ years of experience in data science or analytics roles, preferably in product, web, customer care, or customer experience analytics.
• Strong proficiency in SQL and experience working with large-scale data platforms (e.g., Spark, Databricks, BigQuery, Redshift).
• Experience using BI and visualization tools (e.g., Tableau, Qlik, Dash) to deliver clear, stakeholder-ready insights.
• Solid experience with experimentation and causal analysis (e.g., A/B/n testing, applied causal methods), with good judgment on when and how to apply them.
• Familiarity with AI/ML and GenAI-enabled analytics, and the ability to reason about implications for measurement, experimentation, and user behavior.
• Strong business acumen, with the ability to translate business questions into testable hypotheses and actionable insights.
• Excellent data storytelling and communication skills, with the ability to influence decisions across technical and non-technical audiences.
• Comfortable working in a fast-paced, ambiguous environment, with flexibility to shift priorities and collaborate across cross-functional teams.

What Success Looks Like in This Role

• Delivers insights that stakeholders trust and use to make decisions.
• Identifies flawed assumptions or incomplete framing before analyses are shared.
• Balances analytical rigor with speed and pragmatism.
• Collaborates effectively across functions to drive impact.

Why Join Us

You’ll work on problems at the intersection of learning, analytics, and customer success, with the opportunity to influence how experts are trained and enabled at scale. This role offers meaningful impact, strong cross-functional exposure, and room to grow.

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 $ 162,500- 220,000

Southern California $ 149,500- 202,500

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