Pay
$118K–$193K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 3,721 postings in the last year. Stated ranges, not salaries paid.
San Diego, California, United States; Mountain View, California, United States
Actively hiring, first seen by us 2 days agoIntuit 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- $220,000Read the full posting
Design, build, and deploy scalable predictive and uplift models, including LTV and time-series forecasting
Own the end-to-end experimentation pipeline, from hypothesis design to impact quantification
Lead causal inference and econometric analyses of key business growth levers
Define and evolve success metrics that are predictive and causally informative
Present data-driven strategy recommendations to VP and Director stakeholders
Design, build, and deploy scalable models—including ensemble methods, time-series forecasting, LTV modeling, deep learning architectures, and uplift modeling
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.
Lead causal inference and econometric analyses to understand and influence key levers of business growth
Define and evolve success metrics using state-of-the-art measurement frameworks, ensuring that business KPIs are both predictive and causally informative.
Deliver compelling, data-driven narratives to VP and Director stakeholders
This role requires a foundation in statistical methods, machine learning, experimentation design, and causal inference
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.
Actively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
$118K–$193K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 3,721 postings in the last year. Stated ranges, not salaries paid.
Day 2
Early. Similar jobs usually come down between day 7 and day 55.
From 10,000 similar postings that came down. Coming down is not always a hire.
62 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
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 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.
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Yes. We’ve followed 2 other Senior Data Scientist jobs there since April 2026. 2 came down, usually after about 35 days.
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
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:Selected passages from the saved posting. Check the full description for conditions and exceptions.
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
San Diego, California, United States; Mountain View, California, United States
Working pattern and location restrictions need checking in the full posting.
No clear work-authorization passage found. Eligibility is unconfirmed.