Director of Data, Builder.ai

Situation

VC-backed AI SaaS company in a hyper-growth phase, scaling through Series B to D. Data was fragmented, reporting was manual, and there was limited visibility into subscription metrics.

Stakes

Series B through D fundraising rounds depend on investor-grade metrics (ARR, MRR, churn, LTV, CAC). Without a data organisation, every round meant re-deriving these numbers manually under time pressure.

My Role

Built and led the Data & Analytics division from a single hire to fifteen, covering engineering, BI and data science.

Decision

Unified the data stack and built board-level dashboards as permanent infrastructure rather than one-off fundraising deliverables, so the same system served engineering, finance and the board.

Execution

• Built the Data & Analytics organisation from 1 to 15 people
• Unified a fragmented data stack into a single source of truth for subscription metrics
• Led AI initiatives: an AI-powered chatbot ("Natasha") and a Neo4j knowledge graph migration

Outcome

• Board dashboards for ARR, MRR, churn, LTV, CAC and forecasting directly supported Series B–D fundraising
• 75% reduction in manual finance and product reporting effort
• AI chatbot and knowledge graph capabilities launched in production