Overview
Overview
We are seeking a Staff Data Scientist to join our Money Data Science Team. This role is focused on growth across Intuit's fast money and consumer lending products. This is a high-impact role where your work will directly influence product, marketing, and business 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 and contribute to 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.
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.
Leadership and Ownership: Demonstrate boundaryless leadership and extreme accountability - proactively drives outcomes across teams and leads with influence, not authority.
Team Development: Serve as the technical lead for cross-team data science projects, ensuring best practices and mentoring junior data scientists
Qualifications
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.
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.
Leadership and Ownership: Demonstrate boundaryless leadership and extreme accountability - proactively drives outcomes across teams and leads with influence, not authority.
Team Development: Serve as the technical lead for cross-team data science projects, ensuring best practices and mentoring junior data scientists
Qualifications
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.
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position will 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 (https://www.intuit.com/careers/benefits/full-time-employees/) ). 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:
EOE AA M/F/Vet/Disability. Intuit will consider for employment qualified applicants with criminal histories in a manner consistent with requirements of local law.
