Head of Sales Data Science & Analytics

About Gusto

At Gusto, were on a mission to grow the small business economy We handle the hard stuff — payroll, health insurance, 401(k)s, and HR — so owners can focus on their craft and their customers

With teams in Denver, San Francisco, and New York, we support more than 500,000 small businesses nationwide and are building a workplace that reflects the people we serve.

All full-time employees receive competitive base pay, benefits, and equity (RSUs) — because everyone who helps build Gusto should share in its success. Offer amounts are determined by role, level, and location. Learn more about our Total Rewards philosophy .

AI is a fundamental part of how work gets done at Gusto. We expect all team members to actively engage with AI tools relevant to their role and grow their fluency as the technology evolves. AI experience requirements vary by role and will be assessed during the interview process.

About the Role

Gusto is looking for an experienced Senior Data Science Leader to empower our Sales Data team, the team that powers the insights, forecasting, and measurement infrastructure behind how we acquire, expand, and retain our revenue base.

We expect this leader to be both a strategic partner and execution-focused. Youll guide senior sales and marketing leaders through complex analytical questions, develop analysts into statistical and scientific thinkers, and collaborate cross-functionally with stakeholders across Sales Operations, Data Engineering, Finance, R&D, and more.

As AI tooling becomes deeply embedded in Gustos data infrastructure, the nature of analytics work is fundamentally shifting Tasks that once consumed a significant portion of our analysts time, such as reporting, dashboard maintenance, and answering ad hoc questions, are increasingly handled by a maturing self-serve ecosystem

What remains are the hard problems: ones that require rigorous statistical thinking, causal reasoning, and the ability to draw defensible conclusions in messy, real-world conditions where controlled experiments arent always possible.

This role has two equally important mandates The first is operational: Gustos sales data foundation has significant technical debt, and this leader will need to partner closely with Data Engineering to assess the current state, architect a modern and scalable data layer, and execute a phased remediation

The second is transformational: as the foundation gets rebuilt, this leader must simultaneously evolve what the team does with it: moving from a function defined by query fulfillment and reactive reporting toward one defined by advanced forecasting capabiliti