Senior Data Scientist

Intuit

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Quick summary

Work type: On-site
Location: San Diego, CAMountain View, CA
Salary: $149,500–$202,500 / yr
Posted: 139 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $158k

This role $176k

$98k $216k

below market most similar roles pay here above market

This role pays more than 68% of similar roles. Most pay $126,800–$189,187 — the blue band above. At the midpoint, this role pays about $176k versus about $158k for comparable roles.

Based on 240 similar postings.

Employer

About Intuit

Intuit is a financial software company known for products like TurboTax, QuickBooks, Mint, and Credit Karma, helping consumers and small businesses manage their finances and taxes. Industry: Financial Software & Technology

Intuit currently has 255 open roles on FindRole.

Listed pay typically runs $202,500–$274,000 across 236 roles with salary data.

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At a glance

TL;DR · Senior Data Scientist

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The Senior Data Scientist joins the Intuit Customer Success team within the Expert Network to drive AI strategy for product support and live experiences. This role involves architecting analytical frameworks and modeling solutions to optimize human resources through AI-driven innovation. Key responsibilities include designing and deploying scalable models such as ensemble methods, time-series forecasting, LTV modeling, and deep learning architectures. The candidate will own the experimentation pipeline using CUPED, multi-armed bandits, and Bayesian Inference while leading causal inference and econometric analyses. Required technical skills include expert proficiency in SQL, Python, or R, along with experience in Generative AI and data visualization tools like Tableau or Qlik. The role focuses on solving business growth problems through personalization, recommendation systems, and AI-assisted UX.

What does a Data Scientist earn in California?

Median $214500 from 114 postings across 26 companies.

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Skills

Machine Learning Causal Inference Python SQL R Generative AI Experimentation Design Deep Learning Time-series Forecasting Uplift Modeling Tableau Qlik Bayesian Inference Multi-armed Bandits CUPED Econometrics Data Visualization

What you'll do

Design, build, and deploy scalable machine learning models including ensemble methods, time-series forecasting, and deep learning architectures.
Own the end-to-end experimentation pipeline from hypothesis generation to rigorous causal interpretation and impact quantification.
Lead causal inference and econometric analyses to identify and influence key levers of business growth.
Define and evolve success metrics using state-of-the-art measurement frameworks to ensure KPIs are predictive and causally informative.
Deliver data-driven narratives and actionable strategy recommendations to VP and Director level stakeholders.
Architect analytical frameworks and modeling solutions in partnership with Product, Engineering, and Customer Success teams.
Integrate ML models into production environments for personalization, recommendation, and AI-assisted user experiences.

What we're looking for

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.