i like turning messy customer feedback into something workable.
Data analyst focused on product insights: VoC text analytics, funnels, cohorts, and experiment readouts. I ship reproducible analyses that plug into BI
Languages: Python, SQL, Excel (advanced) Data Stack: pandas, numpy, seaborn, pingouin, matplotlib, Jupyter, BigQuery, GA4 Viz & BI: Tableau, Power BI, Looker Studio Ecommerce: Shopify, Klaviyo, survey tooling Ops: Git, GitHub, Notion, Slack
Languages (human): English (TOEFL IBT 111/120), Spanish (native), French (intermediate, france study exchange)
Voice of Customer Intelligence
- Classify open text by sentiment and themes
- Export Excel or BI-ready tables with charts for non-technical partners
Product Analytics
- KPI design, funnels, retention cohorts, lightweight LTV
- Clean executive readouts that drive a decision
Experimentation
- Guardrails, lift estimates, and concise one-pagers
- Comfort with CUPED style variance reduction and power checks
- Faster VoC triage across multilingual feedback
- Tighter spec for an analytics “operating manual” that keeps outputs Excel-ready and reproducible
- Email: sylvizamorat@gmail.com
Berry fact: zarzamora means blackberry. Aggregate fruits. Aggregate metrics. Coincidence.