Staff Data Scientist

Staff Data Scientist

Join the Intuit Customer Success team as a Staff Data Scientist within our Expert Network. In this role, you will help shape the AI strategy for our product support and live experiences. You'll be central to optimizing our greatest resource, our people, through innovating, experimenting, learning, pivoting, and scaling AI-driven solutions.

This is a mission-critical role requiring a strategic thought partner who brings cutting-edge data science techniques and deep domain expertise to influence our Customer Success strategy and drive business growth at scale. You will partner directly with cross-functional leaders—across Product Management, Engineering, Data, Customer Success, and Service Delivery—to architect the analytical frameworks and modeling solutions that shape our Expert Network and our AI Driven platform.

This role demands a strong foundation in statistical methods, machine learning, experimentation design, and causal inference, coupled with a demonstrated ability to lead with influence, navigate ambiguity, and execute with precision.

Responsibilities

• Advanced Predictive Modeling & Machine Learning: Design, build, and deploy scalable models—including ensemble methods, time-series forecasting, LTV modeling, deep learning architectures, and uplift modeling—to uncover high-impact growth opportunities and drive personalization.
• Experimentation Science & Design: Own the end-to-end experimentation pipeline—from hypothesis generation and design (e.g., CUPED, multi-armed bandits, Bayesian Inference) to rigorous causal interpretation and impact quantification.
• Causal Inference: Lead causal inference and econometric analyses to understand and influence key levers of business growth with a crisp understanding of incremental impact.
• Metric Design & Impact Attribution: Define and evolve success metrics using state-of-the-art measurement frameworks, ensuring that business KPIs are both predictive and causally informative.
• Communication: Deliver compelling, data-driven narratives to VP and Director stakeholders; distill complex findings into clear, actionable strategy recommendations with quantified business impact.
• ML Engineering & Native AI: Collaborate with the Central AI team to productionalize models that enhance personalization and automation throughout the user experience.
• Thought Leadership & Mentorship : Mentor senior data scientists and establish best practices in experimental design, model validation, and responsible AI usage; drive a culture of analytical excellence and scientific rigor.
• Strategic Influence: Demonstrate extreme ownership across cross-functional initiatives, influencing product vision and delivering measurable impact through analytics innovation.

Qualifications

• Master's or PhD degree in Computer Science, Statistics, Econometrics, Data Science, or a quantitative field.
• 7+ years of progressive experience in applied data science roles with increasing scope and complexity.
• Proven experience applying state-of-the-art machine learning and causal inference methodologies in high-impact, product-facing applications.
• Expert-level proficiency in SQL as well as Python or R
• Demonstrated success integrating ML models into production environments, especially within personalization, recommendation, or AI-assisted UX.
• Deep understanding of Generative AI and other evolving technologies. Application of GenAI at scale in a production environment
• Deep knowledge of experimental design, including non-standard A/B testing methods, uplift modeling, and sequential testing frameworks.
• Hands-on experience with data visualization tools like Tableau or Qlik.
• Strong communication and storytelling abilities—adept at translating sophisticated analytics into strategic guidance.
• Proven leadership in mentoring technical talent and driving cross-team alignment through data science innovation.