Senior Data Scientist at Intuit

Job description

Join the Intuit Customer Success team as a Senior Data Scientist within our Expert Network. In this role, you will help drive the AI strategy for our product support and live experiences. You’ll be a key member in optimizing our greatest resource, our people, through innovating, experimenting, learning, and scaling AI-driven solutions. In this role you will bring cutting-edge data science techniques to influence our Customer Success strategy and drive business growth at scale. You will partner directly with cross-functional teams—across Product Management, Engineering, Data, Customer Success, and Service Delivery—to architect the analytical frameworks and modeling solutions that drive our Expert Network and our AI Driven platform. This role requires a 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. Strategic Influence: Demonstrate extreme ownership across cross-functional initiatives, influencing product vision and delivering measurable impact through analytics innovation. Qualifications Master’s degree in Computer Science, Statistics, Econometrics, Data Science, or a quantitative field. 4+ 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 to accelerate insights 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. 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: San Diego $149,500 - $202,500 Mountain View, CA $162,500- $220,000

Requirements

Must-haves

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.
Strategic Influence: Demonstrate extreme ownership across cross-functional initiatives, influencing product vision and delivering measurable impact through analytics innovation.
Master’s degree in Computer Science, Statistics, Econometrics, Data Science, or a quantitative field.
4+ 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 to accelerate insights
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.
San Diego $149,500 - $202,500
Mountain View, CA $162,500- $220,000

Nice-to-haves

None flagged.

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Keywords to mirror

aimachine learningsqlpythonml

Platform: career-feeds
Effort: medium

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