Intuit
Join the Intuit Customer Success team as a Lead Data Scientist within our Expert Network. In this exciting role, you will be instrumental in shaping our AI strategy for product support and live experiences. You will play a key role in optimizing our most valuable asset—our talented team—by innovating, experimenting, learning, and scaling AI-driven solutions.
As a Lead Data Scientist, you will leverage advanced data science techniques to influence our Customer Success strategy and drive significant business growth. Collaborating closely with cross-functional teams across Product Management, Engineering, Data, Customer Success, and Service Delivery, you will architect analytical frameworks and modeling solutions that enhance our Expert Network and AI-driven platform.
This role demands a solid foundation in statistical methods, machine learning, experimentation design, and causal inference. You will need to demonstrate the ability to lead with influence, navigate through ambiguity, and execute strategies with precision.
Key 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 identify impactful growth opportunities and enhance personalization. Experimentation Science & Design:
Take ownership of the complete 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 clear understanding of incremental impact. Metric Design & Impact Attribution:
Define and evolve success metrics using state-of-the-art measurement frameworks, ensuring business KPIs are predictive and causally informative. Communication:
Present compelling, data-driven narratives to VP and Director stakeholders, distilling complex findings into clear, actionable strategy recommendations backed by quantified business impact. Strategic Influence:
Exhibit extreme ownership across cross-functional initiatives, influencing product vision and delivering measurable impact through analytical innovation. Qualifications:
Master's degree in Computer Science, Statistics, Econometrics, Data Science, or related quantitative field. 3+ years of progressive experience in applied data science roles with increasing complexity. Proven expertise in applying advanced 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 in integrating ML models into production settings, particularly within personalization, recommendation, or AI-assisted user experiences. Deep understanding of Generative AI and emerging technologies to accelerate insights. Robust 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. Intuit offers a competitive compensation package with a strong pay-for-performance rewards approach. This position is eligible for cash bonuses, equity rewards, and benefits in accordance with our plans and programs. The expected base pay range for this position is: Bay Area California: $159,500 - $215,500 Southern California: $149,500 - $202,500
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 identify impactful growth opportunities and enhance personalization. Experimentation Science & Design:
Take ownership of the complete 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 clear understanding of incremental impact. Metric Design & Impact Attribution:
Define and evolve success metrics using state-of-the-art measurement frameworks, ensuring business KPIs are predictive and causally informative. Communication:
Present compelling, data-driven narratives to VP and Director stakeholders, distilling complex findings into clear, actionable strategy recommendations backed by quantified business impact. Strategic Influence:
Exhibit extreme ownership across cross-functional initiatives, influencing product vision and delivering measurable impact through analytical innovation. Qualifications:
Master's degree in Computer Science, Statistics, Econometrics, Data Science, or related quantitative field. 3+ years of progressive experience in applied data science roles with increasing complexity. Proven expertise in applying advanced 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 in integrating ML models into production settings, particularly within personalization, recommendation, or AI-assisted user experiences. Deep understanding of Generative AI and emerging technologies to accelerate insights. Robust 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. Intuit offers a competitive compensation package with a strong pay-for-performance rewards approach. This position is eligible for cash bonuses, equity rewards, and benefits in accordance with our plans and programs. The expected base pay range for this position is: Bay Area California: $159,500 - $215,500 Southern California: $149,500 - $202,500