Staff Data Scientist

Intuit

Quick summary

Work type
On-site
Location
San Diego, CAMountain View, CA
Posted
4 days ago
Nearby
99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $158k
$87k most similar roles pay here $212k

This listing doesn't post a salary. Most similar roles pay $126,800–$190,075.

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 125 open roles on FindRole.

Listed pay typically runs $200,750–$272,000 across 112 roles with salary data.

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At a glance

TL;DR · Staff Data Scientist

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As a Staff Data Scientist on the Intuit Customer Success team, you will play a pivotal role in shaping the AI strategy for product support and live experiences. Your responsibilities include designing and deploying scalable machine learning models to optimize resource allocation and drive personalization, while also leading causal inference analyses and experimentation science to measure business impact accurately. You will collaborate with cross-functional teams to integrate advanced analytics into production environments, ensuring that ML models enhance user experience and contribute to strategic decision-making. This role requires expertise in Python or R, SQL, and a deep understanding of cutting-edge data science techniques such as ensemble methods, time-series forecasting, and uplift modeling. With a focus on Generative AI and experimental design, you will mentor senior data scientists and drive analytical excellence across the organization.

Skills

Python R SQL Tableau Qlik AWS Kubernetes CI/CD CUPED Bayesian Inference Generative AI Machine Learning Deep Learning Ensemble Methods Time-Series Forecasting LTV Modeling Uplift Modeling Multi-Armed Bandits Causal Inference Econometrics

What you'll do

  • Design, build, and deploy scalable machine learning models to uncover high-impact growth opportunities.
  • Own the end-to-end experimentation pipeline including hypothesis generation, design, and causal interpretation.
  • Lead causal inference analyses to understand key levers of business growth with incremental impact insights.
  • Define success metrics using advanced measurement frameworks to ensure predictive and causally informative KPIs.
  • Mentor senior data scientists in experimental design, model validation, and responsible AI usage practices.

What we're looking for

  • Master’s or PhD degree in a quantitative field like Computer Science, Statistics, or Data Science.
  • 7+ years of progressive experience in applied data science roles with increasing complexity.
  • Expertise in applying advanced machine learning and causal inference methodologies to high-impact applications.
  • Proficiency in SQL and Python/R for model deployment in production environments.
  • Deep knowledge of experimental design including non-standard A/B testing methods and sequential testing frameworks.
  • Hands-on experience integrating Generative AI technologies at scale in a production environment.
  • Strong communication skills to translate complex analytics into strategic guidance for senior stakeholders.

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