Role overview
Come join the QB Live Data Science team as a Staff Data Scientist. Our team works cross functionally to improve and accelerate decision-making across the Expert Segment by surfacing data, insights, and strategic thinking that address our most critical customer and business problems. The Expert Segment's goal is to connect small businesses with expert guidance to help them run their operations more effectively, from education on bookkeeping to enabling insightful reporting on the platform.
This role offers the opportunity to shape how data drives decision-making for a critical segment of Quickbooks, influencing product strategy at scale while partnering with stakeholders across product, engineering, and marketing.
What you'll work on
- Develop and apply advanced analytical methodologies and predictive models across large-scale, diverse datasets to inform strategic decisions and drive business growth.
- Lead end-to-end product experimentation, including hypothesis development, experimental design, configuration, analysis, visualization, and action planning.
- Synthesize and translate data from multiple sources into clear, actionable insights and recommendations for business stakeholders.
- Solve complex business problems using statistical analysis, segmentation, funnel analysis, and modeling techniques.
- Identify and uncover new business opportunities through exploratory data analysis and research.
- Communicate KPI performance and analytical findings to stakeholders, providing guidance on interpretation and enabling effective use of insights to inform decisions.
- Mentor and influence junior data scientists and analysts in the organization
What we're looking for
6+ years of experience working in product, marketing, web, or other related data science & analytics fields.
Highly proficient in SQL, Tableau, and Excel
Ability to derive insights, tell stories with data, educate effectively, instill confidence in recommendations, and motivate others to act on them
Experience with programming languages including R or Python
Ability to pull and manipulate data including building ETL/data pipelines to support analytics use cases with advanced SQL and data warehousing knowledge
Statistical knowledge to guide and support A/B testing or other experimentation frameworks, and interpret the results to draw detailed and practical conclusions
Experience in modeling or business application/evaluation of machine learning
Excellent problem-solving skills and end to end quantitative thinking
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). 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: $186,500 - $252,000.