Head of Sales Data Science & Analytics

gusto; United States; Hybrid; USD 190,000 - 240,000; Full time

Benefits offered by this job

Hybrid work model

Equity (RSUs)

Office in Denver/San Francisco/NewYork

Job summary

Gusto is seeking a senior data science leader to head its sales analytics organization, powering insights, forecasting, and measurement for revenue growth across acquisition, expansion, and retention.

You will rebuild a debt-laden data foundation with data engineering, advance forecasting methods, and develop a team of scientists and analysts who partner with revenue, operations, and engineering leaders.

Qualifications

• 10+ years of experience in data science or related fields, with at least 4 years leading a growing analytics team.
• Builder-minded leader who develops people and can dive into reports, analyses, and troubleshooting.
• Strong command of experimental design, causal reasoning, and quasi-experimental methods with ability to explain tradeoffs to non-technical stakeholders.
• Deep experience with CRM data at scale, including extraction strategies, warehouse reconciliation, and treating CRM as truth.
• Proven track record rebuilding tech-debt-laden data environments for long-term scalability.
• Strong SQL skills and hands-on depth, with a history of building analytics in a high-growth SaaS/tech environment.

Responsibilities

• Set vision for and lead a team of data scientists and analysts delivering impact across customer acquisition and product expansion sales motions.
• Conduct deep-dive analyses to surface revenue drivers and anomalies, translating findings into clear recommendations for senior leadership and partners.
• Partner with data engineering and platform teams to architect a modern scalable sales data layer and execute remediation.
• Align with revenue, sales operations, and platform engineering on a shared data and infrastructure roadmap.
• Evolve forecasting with more rigorous approaches such as propensity scoring and seasonality controls.
• Leverage AI-first development to build self-service analytics and coach the team to raise analytical rigor.

Skills

Team leadership

SQL

CRM data

Causal inference

Experiment design

SaaS analytics

Stakeholder communication

Job description

Role overview

A senior data science leader is needed to head a sales analytics organization that powers the insights, forecasting, and measurement infrastructure behind how a high-growth SaaS business acquires, expands, and retains its revenue base. The role carries two equal mandates: rebuilding a tech-debt-laden sales data foundation alongside data engineering peers, and transforming the team from reactive query fulfillment toward rigorous forecasting, causal inference, and statistical thinking. The leader will serve as a strategic partner to senior revenue, operations, and engineering stakeholders while developing a team of scientists and analysts.

Responsibilities

• Set vision for and lead a team of data scientists and analysts delivering impact across customer acquisition and product expansion sales motions.
• Conduct deep-dive analyses to surface revenue drivers and anomalies, translating complex findings into clear, actionable recommendations for senior leadership and cross-functional partners.
• Partner with data engineering and platform teams to assess current systems, architect a modern scalable sales data layer, and execute a phased remediation.
• Align with senior revenue, sales operations, and platform engineering leaders on a shared data and infrastructure roadmap.
• Evolve forecasting methodology by incorporating more rigorous approaches such as propensity scoring and improved seasonality controls.
• Leverage AI-first development to build self-service analytics capabilities for operations partners, while recruiting, developing, and coaching team talent to raise analytical rigor across the function.

Requirements

• 10+ years of experience in data science or related fields, with at least 4 years leading a growing analytics team.
• Builder-minded leader who develops people and maintains a roll-up-your-sleeves attitude, able to step into details to build reports, run analyses, and troubleshoot when needed.
• Strong command of experimental design, causal reasoning, and quasi-experimental methods (e.g., difference-in-differences, synthetic control, regression discontinuity, propensity score matching), including the ability to communicate tradeoffs of observational causal claims to non-technical stakeholders.
• Deep experience working with CRM data at scale, including extraction strategies, warehouse reconciliation, and treating CRM systems as a source of truth.
• Proven track record of inheriting messy, tech-debt-laden data environments and rebuilding foundations with long-term scalability in mind.
• Strong SQL skills and hands-on technical depth, plus a track record of building analytics functions in a high-growth SaaS or technology environment.

Nice to have

• Experience applying AI tooling to analytics workflows and building self-service data products for operations partners.
• Background supporting both customer acquisition and expansion sales teams in a fast-scaling subscription business.

Benefits and work setup

• Competitive base salary, benefits, and equity (RSUs), with final offer determined by experience and location.
• Hybrid work model with physical offices in Denver, San Francisco, and New York City; in-office expectation approximately 2-3 days per week depending on role.
• Secure, reliable internet connection required for remote workdays.