Principal Data Scientist, Workforce Solutions (GBSG)

Intuit's Global Business Solutions Group (GBSG) builds the platform that powers prosperity for millions of solo, small and mid-market businesses. Workforce Solutions — QuickBooks Payroll, Time, Benefits, and Contractor Payments — is how that platform serves the people those businesses employ, and it is one of the fastest-growing, highest-retention parts of the QuickBooks ecosystem.

We are looking for a curious, influential, and deeply strategic data scientist to set the data science direction for Workforce Solutions and accelerate its growth.

This is a principal-level individual contributor role. You will operate across the entire Workforce portfolio — partnering directly with Product, Product Marketing, Design, Engineering, and Finance leaders — and be accountable for the data-backed point of view that shapes the multi-year Workforce roadmap. You will define how we measure growth for this business, decide which questions are worth answering, and bring the rigor that turns ambiguous strategic bets into testable, sized hypotheses. Success looks like Director and VP leaders changing their plans because of the work you put in front of them.

Responsibilities

Own the data science strategy for Workforce Solutions end to end: decompose the growth thesis for payroll, time, and benefits into the measurable drivers underneath it, identify the critical assumptions in the plan, size their sensitivity, and design the measurement that resolves them

Drive attach, activation, and retention growth across the Workforce portfolio through deep analysis of customer behavior — from the moment a QuickBooks customer hires their first employee through run-rate payroll, time tracking, and benefits adoption

Set the experimentation bar for the business unit: design and adjudicate high-stakes tests, apply causal methods where clean experiments aren't possible (quasi-experimental designs, synthetic control, difference-in-differences, uplift modeling), and establish the standards other data scientists build against

Define and own the metric system for Workforce Solutions — the canonical definitions of attach, seat growth, engagement, and retention that Product, Finance, and leadership all plan against

Synthesize business performance narratives for the portfolio, clearly articulating the unified story on growth drivers, headwinds, and the actions that move them

Build durable understanding of Workforce customer segments and their path to growth, translating it into a prioritized set of product and go-to-market bets

Own the data architecture and instrumentation that power clean views on Workforce performance; extend it with new data sources and technology integrations, increasingly powered by agentic systems

Raise the craft of data science across the organization — mentoring senior and staff data scientists, setting technical standards, and multiplying the impact of the broader team without formal management responsibility

Qualifications

10+ years in data science or analytics with a track record of setting strategy and driving outcomes at the business-unit level, across multiple initiatives and partner organizations

Deep expertise in causal inference and experimentation: experimental design and analysis at scale, plus fluency in quasi-experimental and observational causal methods for the many cases where a clean A/B test isn't possible

Proven ability to direct product and growth roadmaps and influence strategy with data-backed hypotheses — not just to answer questions, but to decide which questions matter

Exceptional tops-down executive communication: proven ability to construct a data narrative in dynamic, ambiguous situations and hold the room with Director, VP, and SVP-level leaders

Ability to partner with XFN leaders and advocate for DS programs with significant downstream dependencies; owns prioritization and execution across a broad portfolio

Deep strategic and business management thinking, with working knowledge of subscription growth, unit economics, and product-led growth dynamics

Advanced SQL and Python, hands-on instrumentation and pipeline/ETL construction, and comfort working directly in large, multi-source enterprise data

Demonstrated ability to mentor and elevate senior data scientists and set technical standards for a team

Experience in payroll, HR technology, fintech, or another compliance-heavy domain is a plus; experience building and shipping AI agent systems is a plus

BS or MS in Statistics, Mathematics, Economics, Econometrics, Operations Research, Computer Science, Engineering, Business or a related quantitative field, or equivalent work experience. Advanced degree preferred.

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.

The expected base pay range for this position is:
Mountain View $247,500 - $335,000
San Diego, CA $241,000- $326,500