Senior Data Scientist

Intuit Inc.; San Diego (CA); On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

Cash bonuses

Equity rewards

Benefits package

Job summary

Intuit Inc. is seeking a Senior Data Scientist for its Customer Success team in San Diego, California. You will help redefine AI strategy and apply advanced data science techniques to drive business growth, working with cross-functional teams.

This role involves predictive modeling, experimentation design, and causal inference to inform both strategic decisions and measurable outcomes. Ideal candidates will have a Master’s degree and 4+ years of relevant experience.

The position offers competitive compensation, potential for bonuses, and a focus on fair pay across demographics.

Qualifications

• 4+ years of progressive experience in applied data science roles.
• Expert-level proficiency in SQL and Python or R.
• Deep understanding of Generative AI and experimental design.

Responsibilities

• Design, build, and deploy scalable predictive models.
• Own the end-to-end experimentation pipeline.
• Lead causal inference analyses to influence business growth.

Skills

Machine Learning

Causal Inference

Statistical Methods

Data Visualization (Tableau, Qlik)

Python or R

SQL

Education

Master’s degree in Computer Science, Statistics, Econometrics, Data Science, or a quantitative field

Tools

Tableau

Qlik

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 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: