Staff Data Scientist

Company Overview

Job Overview

We are seeking an experienced Staff Data Scientist to join our Business Strategy Data Science Team. This role is focused on growth across Intuit’s consumer ecosystem of TurboTax and CreditKarma. This is a high-impact role where your work will directly influence product, marketing, and business model strategies.

As a Staff Data Scientist, you will serve as a strategic thought partner to cross-functional leaders, bringing deep analytical expertise and business acumen to bear on Intuit’s most critical growth questions. You’ll lead projects that require advanced econometric modeling, causal inference, and experimental design. You will deliver insights that guide investment decisions, optimize user journeys, and inform strategy at the highest levels. This is a unique opportunity to apply your passion for data and causal reasoning to shape the future of financial empowerment for millions of users.

Responsibilities

• Define KPIs and Success Metrics: Establish key business indicators for projects, ensuring alignment with company objectives and clear measures of success.
• Causal Inference: Lead causal inference and econometric analyses to understand and influence key levers of business growth with a crisp understanding of incremental impact.
• Experimentation: Design, implement, and analyze experiments and quasi-experiments to measure the impact of new initiatives in product and marketing.
• Predictive Analytics and Modeling: Develop predictive models and methodologies to uncover growth opportunities and support long-term business planning.
• Communication: Translate complex technical findings into clear, actionable insights for senior leadership, including product, finance, and marketing executives.
• Mentorship: Mentor junior team members and help shape the team’s analytical rigor and methodology standards in causal inference and A/B testing.
• Leadership and Ownership: Demonstrate boundaryless leadership and extreme accountability - proactively drives outcomes across teams and leads with influence, not authority.

Qualifications

• A bachelor's degree in Statistics, Economics, Computer Science or a related quantitative field is required. Advanced degrees, particularly a Master's or PhD in economics or statistics, are highly desirable.
• At least 5 years of experience applying statistical / econometric and modeling skills in decision making.
• Demonstrated expertise in causal inference—including but not limited to advanced experimentation, synthetic controls, regression discontinuity, and instrumental variables—with a track record of rigorously solving problems with these methods.
• Applied experience leveraging machine learning—including but not limited to predictive forecasting, explainable ML, and end-to-end model pipeline development—to drive meaningful business impact
• A demonstrated ability to navigate through ambiguity and deliver results that significantly impact the business.
• Excellent communication skills and the ability to work effectively with both technical and non-technical colleagues.
• Proficiency in SQL and a statistical programming language such as Python and/or R.