Staff Data Scientist

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.
• Hands-on experience with data visualization tools like Tableau or Qlik.
• Strong communication and storytelling abilities—adequate at translating sophisticated analytics into strategic guidance.
• Proven leadership in mentoring technical talent and driving cross-team alignment through data science innovation.

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.