Head of GTM Intelligence and Analytics

Skills

About the Role

You will define and document GTM metrics, lead dashboard development, and solve complex revenue analytics problems. You will support operating cadences, reconcile data with finance, product, and data engineering, automate reporting, establish data-quality and model-validation standards, and coach a small analytics team.

Requirements

• 8+ years in analytics
• 4+ years in GTM, sales, or revenue analytics
• Experience leading or coaching analysts
• Advanced SQL and BI/dashboarding skills
• Statistical or predictive modeling experience
• Experience analyzing a usage-based or hybrid commit-plus-usage business
• Experience defining metrics with Finance and Product
• Experience partnering with Data Engineering on source-of-truth data
• Experience supporting QBRs, forecast calls, board reporting, or executive reporting
• Experience communicating complex analysis to executives
• BA/BS degree in engineering, statistics, finance, economics, or another quantitative field preferred
• AI/ML infrastructure, developer tools, or API-first company experience preferred
• Hypergrowth experience preferred
• Metrics-layer, semantic-layer, or analytics-engineering tooling experience preferred
• AI or agentic analysis workflow experience preferred
• Salesforce, billing, and product usage data familiarity preferred

Responsibilities

• Define, document, version, and align critical GTM metric definitions
• Build and maintain official leadership dashboards
• Retire conflicting reports
• Lead churn, retention, propensity, cohort, usage-to-revenue, pipeline conversion, and win-rate analyses
• Turn analysis into recommendations and track outcomes
• Establish model-validation standards
• Ensure accurate, timely, repeatable data and tooling for QBRs, forecast calls, and Pipeline Council
• Track forecast accuracy and pipeline coverage
• Automate recurring reporting packs and reports
• Reconcile bookings, ARR, and consumption with financial plans and reported results
• Define product usage and adoption metrics and connect them to revenue analysis
• Partner on source-of-truth CRM, billing, usage, roster, and quota data models
• Define data-quality checks and escalate gaps
• Manage, coach, and grow analytics team members
• Set standards for analytical quality, documentation, and speed
• Use AI and agentic tooling in analytics

Benefits

• Equity