Head of Revenue Analytics Apex

The Head of Revenue Analytics is responsible for building, owning, and governing Apex Group s global commercial analytics capability, ensuring trusted, actionable, and forward-looking insights drive revenue predictability and growth.

This role owns the revenue analytics layer across Salesforce and the enterprise data platform, while working in close partnership with Apex s Global Analytics function and AI teams to integrate broader data sources, advanced analytics, and predictive insights into the commercial operating model.

The role requires a leader who is technically credible, commercially fluent, and able to bridge enterprise data strategy with frontline sales execution ensuring analytics move from reporting to decisioning and action.

Key Responsibilities

1. Revenue Analytics Ownership & Architecture

• Own the end-to-end revenue analytics domain, including data models, metrics, dashboards, and insight delivery for Sales and CRM.
• Lead the design of scalable revenue data models across pipeline, forecasting, bookings, and performance.
• Own the semantic layer and metric definitions that power executive reporting and operational decision-making.
• Partner with IT and Data Engineering to ensure performance, security, and scalability of the revenue analytics stack.

2. Partnership with Global Analytics Function

• Act as the commercial analytics lead interfacing with Apex s global enterprise analytics team.
• Align revenue analytics requirements with enterprise data standards, tooling, and governance.
• Leverage central analytics capabilities (data science, advanced modeling, data engineering) while retaining clear ownership of revenue-specific outputs.
• Ensure consistency between enterprise-wide analytics initiatives and commercial reporting.

3. Advanced & Predictive Analytics

• Lead the evolution from descriptive and diagnostic reporting to predictive and prescriptive analytics.
• Develop models to forecast pipeline risk, deal slippage, win probability, and revenue confidence.
• Partner with AI and data science teams to:
  • Embed predictive insights into Salesforce and commercial workflows
  • Enable next-best-action recommendations for Sales and CRM
  • Surface risks and opportunities proactively, not reactively
• Champion experimentation and iterative improvement of analytical models.

4. Data Integration & External Data Enablement

• Drive the integration of additional internal and third-party data sources, including:
  • Market and industry data
  • Client and fund-level intelligence
  • Benchmarking and competitive insights
  • Alternative and external signals relevant to revenue generation
• Ensure third-party data is mapped, governed, and made actionable within commercial tools.
• Work with AI and product teams to operationalise insights rather than leaving them in dashboards.

5. Analytics Build & Insight Delivery

• Lead the build of executive dashboards and scorecards for:
  • Forecast accuracy and confidence
  • Pipeline health and conversion
  • Sales productivity and performance
  • Regional, product, and segment trends
• Ensure insights are intuitive, timely, and aligned to commercial decision points.
• Support QBRs, MBRs, and board-level reporting with defensible, consistent analytics.

6. Data Governance, Quality & Trust

• Own revenue data governance, including definitions, standards, lineage, and documentation.
• Establish monitoring and controls for data quality, completeness, and integrity.
• Partner with Sales Ops, Deal Desk, and CRM to drive upstream data discipline.
• Serve as the escalation point for revenue data discrepancies across regions.

7. Leadership & Capability Development

• Build and lead a high-performing Revenue Analytics team.
• Set standards for analytical rigor, documentation, and technical excellence.
• Develop talent capable of operating confidently across data, AI, and commercial stakeholders.