GTM Engineer · Revenue Intelligence · AI-native builder
I help revenue teams move faster by owning the entire stack — from data pipelines to stakeholder insight.
~6 years across B2C, B2B, B2B2C, and B2A revenue motions — patient-driven provider acquisition, corporate and academic partnerships, and venture diligence for early-stage companies.
I bridge raw data infrastructure and revenue execution: ingest and model signals, turn them into ICPs and attribution, and route the right insight to Sales, Marketing, and RevOps. Pipeline is a system output, not a sales activity.
Where I've worked
| Role | Company | Focus |
|---|---|---|
| GTM Data Analyst | Vibrant Wellness | $105M B2B2C — attribution, NL→SQL agent, forecasting |
| Business Analyst – GTM | Skill-Lync (YC W19) | $14M+ ACV — playbooks, churn, unit economics |
| VC Analyst Intern | Energy Innovation Capital | ClimateTech diligence, LLM research intake |
| Data Warehouse Engineer | MAHER Corp | HIPAA-compliant clinical data models |
Education: MS in Business Analytics & Artificial Intelligence — The University of Texas at Dallas
Ingest, model, and activate raw signals into enriched segments stakeholders can act on.
- Semantic data layer and dbt-style models across ClickHouse, BigQuery, and HubSpot
- Spot — natural-language → SQL agent grounded in semantic definitions, with guardrails and reconciliation against trusted rollups
- Lead scoring, ICP construction from acquisition / activation / retention signals, and PLG-style routing workflows
- Agentic BI pipeline: extraction → validation → knowledge graph → reporting (in progress)
Turn messy GTM data into decisions leadership and reps can trust.
- Multi-touch attribution crediting ~$75M ARR across channels (NRR, ARR, APV, ROAS, CPA)
- RFM segmentation, anomaly scoring, and similarity matching for ideal customer profiles
- Patient and provider funnel / journey mapping; cohort slicing by lead source, region, and motion
- Revenue forecasting with stated assumptions and confidence intervals (~$50K/day COGS impact communicated to leadership)
- Resolved a data governance gap that had obscured $2.5M in revenue; co-authored data contracts and dbt migration plans
Ship what revenue teams run on daily — not one-off decks.
- Performance dashboards for PQL / SQL / MQL by segment (Power BI, HubSpot)
- Personalized Next Best Action recommendations at daily, weekly, and monthly granularity
- Automated insight runs vs multi-week baselines (orders, revenue, EOD projections)
- Enriched playbooks for distinct acquisition motions; automated triage when risk signals fire
- Outbound and ops automation via N8N, Zapier, Clay, and Apollo — research → enrichment → CRM sync