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Staff Data Scientist

Category Data Location Mountain View, California Job ID 2025-70426
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Company Overview

Intuit is the global financial technology platform that powers prosperity for the people and communities we serve. With approximately 100 million customers worldwide using products such as TurboTax, Credit Karma, QuickBooks, and Mailchimp, we believe that everyone should have the opportunity to prosper. We never stop working to find new, innovative ways to make that possible.

Job Overview

The Global Business Solutions Group (GBSG) is building a connected end-to-end platform that small and mid-market businesses rely on to run and grow their revenue and profitability.

To better support small businesses with human expertise, the Quickbooks Live Data Science team delivers actionable insights, strategic partnership, and advanced analytical models to fuel decision-making across Product, GTM, and Engineering strategies. We work cross-functionally with Product, Engineering, Finance, Marketing, and Design to turn data into impact.

We are looking for a Staff Data Scientist, who is intellectually curious and extremely self-driven, with a proven track record of leading analytics support for critical or high-growth business areas. The ideal candidate will also have a passion for operationalizing data-driven insights into action through influencing the velocity and quality of learnings, while demonstrating a problem-solving and extreme ownership mindset.

Responsibilities

  • Drive strategic thinking to optimize product and user experience efforts (inclusive of experimentation) for customer journeys, based on customer segments, lifecycle stages, and other critical customer attributes.
  • Promotes a scientific and engineering mindset to analytics. Uplevels team on data science and data engineering practices, and teaches experimentation science and statistical modeling.
  • Partners with cross-functional stakeholders to better understand our users and create a single, accurate view of a customer across businesses to make decisions about how best to acquire/retain them, segment, identify high potential value, and proactively interact with them.
  • Leads the full cycle of iterative big data exploration, including hypothesis formulation, data cleansing, testing, insight generation/visualization, and action planning.
  • Collects, analyzes, and models available data to advance the customer success space and build a broad understanding of the Quickbooks Live customers and relevant customer segments.
  • Pursues data quality, troubleshoots data validation, and sees issues to resolution.
  • Provides guidance and support to business leaders and stakeholders on how best to harness available data in support of critical business needs and goals.
  • Establish best practices including quality assurance, automation, code reviews, quality checks, and anomalies.

Qualifications

  • 7+ years of experience working in web, product, customer/care, strategy, sales, marketing, CRM or other related data science & analytics fields. Experience in B2B marketing/sales analytics is a plus.
  • Proven experience analyzing data from a variety of sources, presenting the data in a clear and concise manner, and create actionable insights
  • Expertise in SQL, Python/R
  • Experience with statistical methods such as regression and hypothesis testing
  • Demonstrated, hands-on experience with data visualization tools, e.g. Looker and Tableau
  • Ability to build relationships, be persuasive and influential within and across immediate working groups
  • Strong product sense with a demonstrated ability to diagnose and solve real product problems.
  • Solid modeling foundation, including hands-on expertise with data mining and statistical modeling techniques such as clustering, classification, regression, tree-based methods, anomaly detection, and natural language processing.
  • Experience with customer segmentation, data enrichment tools and technologies, and personalization at scale.
  • Experience utilizing Generative AI tools for data analysis, modeling, insight generation, and influencing stakeholders.
  • Experience with Causal Inference methods is a big plus
  • Degree in engineering, computer science, information systems or equivalent experience required, Masters/MBA preferred
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We use the technology for good to help small businesses and consumers.

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