Vapi

Data Scientist

• Define and own Vapi's core metric set and build the canonical data model
• Make the GTM funnel measurable from signup and first call through activation, qualification, PoC, closed won, adoption, expansion, and retention
• Own data, dashboards, and narratives for weekly and monthly business reviews and instrument OKRs
• Build and scale the modern data stack, including warehouse, ingestion, transformation, orchestration, and BI
• Ship documented and tested dbt models and enforce data contracts
• Design pipelines for call telemetry, transcript events, usage metering, billing signals, and model performance traces
• Set freshness SLAs, alerting, and on-call coverage
• Build AI/LLM monitoring, model telemetry, and prompt-to-performance observability
• Build canonical and semantic layers and function-specific self-serve dashboards
• Own governance, data quality, definitions, dictionary, lineage, and access controls
• Partner with Security and Legal on retention, residency, PII, voice-data handling, HIPAA, GDPR, CCPA, and customer DPAs
• Support pricing, market expansion, product decisions, customer health, revenue recognition, usage-based billing, investor reporting, pipeline health, territory design, and retention modeling
• Plan headcount, hire the first data engineers and analysts, set quality standards, make build-versus-buy decisions, and manage vendor relationships
• Success milestones include publishing metric definitions and a roadmap in 30 days, canonical ARR/NRR/billable-call models in 90 days, end-to-end GTM measurement and self-serve dashboards in six months, and trusted company-wide data within one year

Head of Data

Engineering Manager

• Lead a team of four engineers across billing, fraud, and outbound telephony
• Partner with the PM for Enterprise & Governance to set priorities and turn the roadmap into reliable delivery
• Coach engineers and own service reliability, on-call, and incident response
• Learn billing, fraud, and outbound telephony systems and assess architecture, service ownership, on-call coverage, and team development needs
• Strengthen planning and delivery routines with Product
• Define service ownership and improve on-call and incident response practices
• Guide architecture and code reviews
• Deliver prioritized system improvements
• Set expectations and growth goals for engineers
• Own engineering delivery for billing, pricing, packaging, fraud, and outbound telephony
• Use delivery and reliability data to prioritize improvements
• Build development plans and identify hiring and system investments needed to scale
• Spend approximately 60–70% of time on people management and 20–30% hands-on building, architecture, and code review

Head of Data

Engineering Manager – Trust & Safety