Head of Sales Data Science & Analytics

Join Gusto as the Head of Sales Data Science & Analytics. In this role, you will lead the Sales Analytics team, drive the evolution of our foundational data systems, and partner with key stakeholders to align on a shared data and infrastructure roadmap. You will also evolve our sales forecasting methodology, enable self-service analytics with AI, and drive team excellence. This position requires a strong understanding of sales and revenue domain knowledge, statistical and causal inference expertise, and experience leading teams through significant transformation.

• Lead the Sales Analytics team, driving vision and championing a team of data scientists and analysts to deliver impact across customer acquisition and product expansion sales teams.
• Rebuild the data foundation in collaboration with Data Engineering and Service Platform partners, driving the evolution of foundational data systems needed to build a world-class sales analytics ecosystem.
• Evolve forecasting capabilities and enable self-service analytics with AI, leveraging Gusto's move toward AI-first development to create self-service analytics capabilities for operations partners.
• AI-forward orientation -- has a clear-eyed view of how AI tooling is reshaping the analyst role. Understands that as self-serve and automation absorb routine reporting and ad hoc work, the value of the team increasingly lives in statistical rigor, causal thinking, and the ability to answer questions that can't be solved with a dashboard. Can articulate that vision compellingly and recruit, develop, and retain talent accordingly
• Statistical and causal inference expertise -- strong command of experimental design, causal reasoning, and quasi-experimental methods (e.g., difference-in-differences, synthetic control, regression discontinuity, propensity score matching) for settings where A/B testing isn't possible. Comfortable navigating the assumptions required to make credible causal claims from observational data, and able to communicate those tradeoffs clearly to non-technical stakeholders
• Sales and revenue domain knowledge -- strong understanding of pipeline management, forecasting, quota and attainment tracking, acquisition and expansion motions, and cross-sell/upsell analytics in a multi-product SaaS environment
• Leadership with a Builder Mindset: A dynamic leader who inspires and develops teams while maintaining a “roll up your sleeves” attitude — able to step into the details when needed to build reports, run analyses, and troubleshoot
• Infrastructure-first mindset -- proven track record of inheriting messy, tech-debt-laden data environments and rebuilding foundations with long-term scalability in mind. Thinks in terms of systems, not patches
• Technical depth -- strong SQL skills, hands-on experience with dbt and Snowflake, comfort navigating transformation logic across multiple layers (Salesforce, BI, dbt, dashboards), and ability to mentor analysts on best practices
• Revenue data systems expertise -- deep experience working with Salesforce data at scale, including understanding data extraction strategies, CRM-to-warehouse reconciliation, and the challenges of treating Salesforce as a source of truth
• The ideal candidate brings deep expertise in Sales data, a commitment to building strong foundations for scale, paired with a genuine command of experimentation and quasi-experimental methods, and can instill these capabilities across the team
• Change management and team development -- experience leading teams through significant transformation, raising performance expectations, coaching analysts toward more strategic work, and making tough talent decisions when needed
• Cross-functional partnership -- ability to negotiate priorities and drive shared roadmaps with platform engineering, data engineering, and sales operations teams. Can go toe-to-toe with service platform managers on technical trade-offs
• Strong communication skills -- experience presenting infrastructure roadmaps and analytical insights to executive stakeholders, translating complex data system challenges into clear business terms
• SaaS/Growth Background: Proven track record of successfully building and leading analytics functions in a high-growth SaaS or technology environment
• 10+ years of experience in data science or related fields, with at least 4+ years leading a growing analytics team