Intuit Senior Data Scientist 

United States, California, San Diego 

977099480

As a Senior Data Scientist, you will partner closely with cross-functional teams across Product, Marketing, Sales, Customer Success, Expert Network, and Finance. You will bring rigor to experimentation, clarity to ambiguous problems, and insight to business decisions—all while contributing to a data-driven culture.

• Partner Across Functions - Collaborate with cross-functional stakeholders to define problems, frame hypotheses, and translate business needs into data science projects with measurable impact.
• Analytics & Insights Generation - Analyze large, complex datasets to derive insights that guide strategy, product development, customer acquisition, and engagement initiatives.
• Experimentation & Impact Measurement - Design and evaluate A/B and multivariate tests, using modern experimentation techniques to quantify the effects of new features and marketing campaigns.
• Model Development & Data Enrichment - Build predictive models and customer segmentation frameworks that inform personalization, targeting, and optimization strategies.
• Dashboarding & Data Storytelling - Develop automated reports and visualizations to surface key metrics. Communicate complex results in a simple and compelling way to technical and non-technical audiences.
• Support Data Infrastructure - Collaborate with engineering and platform teams to define tracking requirements, improve data quality, and ensure the right data is available for analysis.
• Uphold Best Practices - Promote experimentation rigor, model validation, reproducibility, and code quality within the data science community at Intuit.

• 5–7 years of experience in analytics, data science, or quantitative roles within consumer tech, fintech, SaaS, or digital marketing.
• Strong analytical thinking and business acumen with the ability to derive actionable insights from ambiguous and complex data.
• Advanced SQL and Python skills; experience with statistical packages (e.g., pandas, scikit-learn, statsmodels) and data visualization tools such as Tableau or Looker.
• Solid foundation in A/B testing and causal inference techniques (e.g., regression, matching, lift analysis, uplift modeling).
• Familiarity with marketing funnel metrics, channel attribution, or growth experimentation preferred.
• Excellent communication skills; able to translate technical findings into business recommendations and influence decision-making.
• Experience collaborating with cross-functional teams in matrixed environments.
• Bachelor’s degree in a quantitative field required; Master’s degree or higher in Statistics, Data Science, Computer Science, Economics, or a related field preferred.