Senior Manager, Head of Sales Data Science & Analytics

<div class="content-intro"><p style="line-height: 1.2;">&nbsp;</p> <hr> <p><strong>About Gusto</strong></p> <p>At Gusto, we're 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.</p> <p>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<a href="https://gusto.com/about/careers/total-rewards" target="_blank"> <u>Total Rewards philosophy</u></a>.</p> <p>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.</p></div><p><strong>About the Role:</strong></p> <p>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.</p> <p>We expect this leader to be both a strategic partner and execution-focused. You'll 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&amp;D, and more.</p> <p>As AI tooling becomes deeply embedded in Gusto's data infrastructure, the nature of analytics work is fundamentally shifting.&nbsp; Tasks that once consumed a significant portion of our analyst's 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 aren't always possible.</p> <p><strong>This role has two equally important mandates. The first is operational: </strong>Gusto's 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.<strong> The second is transformational: </strong>as the fou