Staff Data Scientist

Job Overview

Intuit’s Global Business Solutions Group (GBSG) is dedicated to serving the needs of more than 2 million small businesses and self-employed customers worldwide. Our mission is to power prosperity around the world by helping customers run their businesses with confidence, save time, and make better decisions—leveraging Intuit’s cloud platform, data, and ecosystem of app partners.

The Data Analytics & Science organization plays a critical role in driving customer growth and retention across GBSG through deep product insights, advanced analytics, and data-driven optimization of marketing and lifecycle strategies. We partner closely with product, marketing, engineering, and finance teams to influence strategy at scale using industry-leading tools, techniques, and best practices.

We are seeking a Staff Data Scientist to join the Audience Personalization & Targeting team. This role requires deep expertise in marketing-centric data modeling, measurement, and optimization, along with the ability to provide technical and strategic leadership. As a Staff Data Scientist, you will shape how we identify, understand, and engage the right customers with the right experiences—driving measurable impact across acquisition, engagement, and retention.

In this role, you will:

• Lead the development of advanced models and analytical frameworks to support audience segmentation, targeting, and personalization across marketing channels
• Inform and influence growth marketing strategy through rigorous measurement, experimentation, and causal analysis
• Partner cross-functionally with marketing, product, engineering, sales, and finance to translate business problems into scalable data science solutions
• Drive alignment on metrics, methodologies, and best practices, raising the overall analytical bar across teams
• Act as a technical thought leader and mentor, contributing to the long-term vision of personalization and targeting at Intuit

Responsibilities

• Lead the design and development of advanced predictive and optimization models used across the QuickBooks marketing site and in-product surfaces to personalize experiences for prospective and existing customers, driving meaningful improvements in acquisition, engagement, and retention.
• Own the measurement and evaluation strategy for personalization, targeting, and growth initiatives, including defining success metrics, experimentation frameworks, and causal methodologies to quantify impact and ROI.
• Partner with marketing, product, and finance to evaluate ROI for new pricing, packaging, and growth strategy initiatives, providing data-driven recommendations to inform investment and prioritization decisions.
• Serve as the analytics and data science lead for large-scale campaigns, experiments, and cross-functional initiatives, ensuring rigorous design, execution, and interpretation of results.
• Influence growth and personalization strategy by translating complex analyses into clear, actionable insights and recommendations for both technical and non-technical stakeholders, including senior leadership.
• Set technical and analytical standards for the team by establishing best practices in modeling, experimentation, and measurement, and mentoring other data scientists to raise the overall quality and impact of work.
• Demonstrate strong judgment and strategic thinking, balancing short-term wins with long-term platform and capability investments, and proactively identifying new opportunities to improve customer relevance and business outcomes.

Qualifications

• MS or PhD in a quantitative field such as Statistics, Mathematics, Economics, Finance, Operations Research, Computer Science, or a related discipline, with 6+ years of hands-on experience in data science, analytics, or applied machine learning roles (or equivalent industry experience).
• Deep expertise in statistical modeling and marketing measurement, with a demonstrated track record of applying these techniques to drive business impact in areas such as personalization, targeting, pricing, experimentation, or growth optimization.
• Strong proficiency in Python or R, and extensive experience working with large-scale data using SQL-based technologies (e.g., SQL, Hive, SparkSQL).
• Solid understanding of customer lifecycle analytics, including acquisition funnels, engagement, retention, and lifetime value modeling.
• Advanced knowledge of machine learning and quantitative methods, including but not limited to regression, classification, clustering, time series, causal inference, econometrics, and optimization techniques.
• Excellent communication and storytelling skills, with the ability to translate complex analyses into clear, actionable insights for both technical and executive audiences.
• Demonstrated ownership and sound judgment, with the ability to independently lead ambiguous, high-impact initiatives from problem definition through execution.

Preferred Qualifications

• Experience building or influencing personalization and targeting systems across marketing channels or in-product experiences.
• Hands-on experience with experimentation platforms, A/B testing, and causal inference techniques in real-world business settings.
• Familiarity with pricing, packaging, or growth strategy analytics in SaaS or consumer software products.
• Experience mentoring or technically leading other data scientists, setting best practices, and raising analytical standards across teams.
• Experience working in a cross-functional environment with product managers, engineers, marketers, and finance partners.

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: $186,500 - $252,000.