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Senior Staff AI Scientist – Business Intelligence

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What you’ll work on

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As a Senior Staff AI Scientist, you will own the AI strategy for BI's target customers, accountants and multi-entity, multi-currency businesses, across Reporting, Scale, FP&A, and Conversational BI, including aspects that span beyond any single team's ownership.

  • Own an end-to-end AI strategy spanning Reporting, Scale, FP&A, and Conversational BI

  • Define reference architectures for AI-native BI systems used across multiple teams

  • Build AI capabilities on BI's data platform, including proprietary evaluation frameworks

  • Decide when to fine-tune, train, or prompt for conversational reporting

  • Lead AI work across multiple teams and represent BI's AI strategy to senior leaders

From the employer’s posting
As a Senior Staff AI Scientist, you will own the AI strategy for BI's target customers, accountants and multi-entity, multi-currency businesses, across Reporting, Scale, FP&A, and Conversational BI, including aspects that span beyond any single team's ownership. You will define the reference architectures and evaluation standards that other AI Scientists across BI build on, and you will represent BI's AI strategy to senior and executive leadership.
Own an end-to-end AI strategy for BI's target customers, spanning Reporting, Scale, FP&A, and Conversational BI
Define reference architectures for AI-native BI systems adopted across multiple teams
Build Intuit's AI advantage in BI through a combination of novel algorithms, Intuit's proprietary financial data, and closed-loop agentic optimization infrastructure, including proprietary evaluation frameworks
such as when to invest in fine-tuning or Intuit LLM training versus prompting for conversational reporting
Lead multiple capabilities or complex application areas across multiple teams

What you’ll bring

All qualifications

Core experience

  • 8+ years of applied ML or data science experience, including significant experience defining technical strategy and architecture across multiple teams or a major organizational initiative.
  • Deep expertise across modern ML and AI paradigms, including LLMs, agentic system design, causal inference, and time-series and forecasting methods, with a track record of translating them into durable production systems at scale.
  • Experience building or influencing data platform strategy for AI/ML at scale, such as OLAP or distributed data engines, feature platforms, or agentic data pipelines.

Preferred experience

  • Experience defining evaluation standards and responsible AI practices in a regulated or high-trust domain; financial data experience strongly preferred.
Qualification wording
8+ years of applied ML or data science experience, including significant experience defining technical strategy and architecture across multiple teams or a major organizational initiative.
Deep expertise across modern ML and AI paradigms, including LLMs, agentic system design, causal inference, and time-series and forecasting methods, with a track record of translating them into durable production systems at scale.
Experience building or influencing data platform strategy for AI/ML at scale, such as OLAP or distributed data engines, feature platforms, or agentic data pipelines.
Experience defining evaluation standards and responsible AI practices in a regulated or high-trust domain; financial data experience strongly preferred.
Education & alternatives
Qualifications - PhD in Computer Science, Statistics, Applied Mathematics, Operations Research, or a related field. - 8+ years of applied ML or data science experience, including significant experience defining technical strategy and architecture across multiple teams or a major organizational initiative.
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Actively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 2, 20262 days ago
Recorded sightings
4
Last seen by us
Nov 5, 2026

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About the role

We file this job under Analyst, by the work the posting describes.

Analysts answer business questions with data. They pull numbers with SQL, build reports and dashboards, and explain what changed and why to the people making decisions.

Most postings ask for SQL, spreadsheets, a dashboard tool such as Tableau or Power BI, and clear writing.

Unlike a data scientist, an analyst mostly explains what happened rather than building models that predict what will.

Job description

View original posting ↗

About the team

Intuit's Business Intelligence (BI) team builds the reporting and analytics experiences that millions of QuickBooks customers and accountants rely on every day, including Modern Reports, Management Reports, KPI Scorecards, Dashboards, and FP&A (Cash Flow, Budgets, Forecasting). The team is in the middle of extending these experiences with AI: conversational reporting through Omni, self-serve report building, and agentic development practices that let us build faster on a codebase spanning years of financial logic. We sit on one of Intuit's largest proprietary datasets, tens of billions of transaction rows across millions of small businesses, and we are scaling our platform (built on StarRocks) to support multi-entity, multi-currency customers at a new order of magnitude.

About the role


As a Senior Staff AI Scientist, you will own the AI strategy for BI's target customers, accountants and multi-entity, multi-currency businesses, across Reporting, Scale, FP&A, and Conversational BI, including aspects that span beyond any single team's ownership. You will define the reference architectures and evaluation standards that other AI Scientists across BI build on, and you will represent BI's AI strategy to senior and executive leadership.


Responsibilities


  • Own an end-to-end AI strategy for BI's target customers, spanning Reporting, Scale, FP&A, and Conversational BI, including aspects that span beyond a single team's ownership.

  • Lead multiple capabilities or complex application areas across multiple teams, identify strategic gaps, and influence technology and product direction across BI and its Mid-Market and SBG stakeholders.

  • Build Intuit's AI advantage in BI through a combination of novel algorithms, Intuit's proprietary financial data, and closed-loop agentic optimization infrastructure, including proprietary evaluation frameworks, built on BI's data platform (the StarRocks-based scale engine and the broader agentic development effort to make the reporting codebase legible to AI).

  • Steer investment decisions in frontier AI approaches for BI, such as when to invest in fine-tuning or Intuit LLM training versus prompting for conversational reporting, govern data contracts and privacy for financial data, and evaluate emergent agent behavior in customer-facing reporting.

  • Define reference architectures for AI-native BI systems adopted across multiple teams, including Reporting, Scale, and Conversational Narrative Builder, treating multi-agent coordination and tool orchestration as first-class design concerns.

  • Craft responsible AI frameworks specific to BI's context, anticipating regulatory and compliance considerations tied to presenting financial data and insights to small businesses and accountants.

  • Identify and resolve systemic issues across BI's technical foundation, such as architectural shortcomings or scale bottlenecks, that limit the org's overall delivery capability.

  • Raise the bar for AI Science quality across BI, typically 10 to 35 individuals, mentor other technical leaders including Staff and Senior AI Scientists, and drive adoption of best practices and agentic tooling org-wide.

  • Represent BI's AI strategy to senior and executive leadership and align investment decisions with business priorities.


Qualifications


  • PhD in Computer Science, Statistics, Applied Mathematics, Operations Research, or a related field.

  • 8+ years of applied ML or data science experience, including significant experience defining technical strategy and architecture across multiple teams or a major organizational initiative.

  • Deep expertise across modern ML and AI paradigms, including LLMs, agentic system design, causal inference, and time-series and forecasting methods, with a track record of translating them into durable production systems at scale.

  • Experience building or influencing data platform strategy for AI/ML at scale, such as OLAP or distributed data engines, feature platforms, or agentic data pipelines.

  • Experience defining evaluation standards and responsible AI practices in a regulated or high-trust domain; financial data experience strongly preferred.

  • Exceptional written and verbal communication skills, with experience presenting technical strategy to VP- or CTO-level stakeholders.

  • A track record of mentoring Staff-level and senior individual contributors, and of building technical roadmaps that span multiple teams and quarters.


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. 

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