Geiseanne Ramos

I’m a detail-oriented, highly analytical Data Analyst with 5+ years of experience translating large datasets into actionable business insights. I build automated dashboards and predictive models that help teams make faster, smarter decisions—driving measurable impact like +28% revenue growth and improved retention.

At Emaga, I conduct exploratory data analysis using Python and SQL to uncover churn patterns, then apply segmentation approaches like Pareto and RFM to identify high-value groups. I design targeted campaigns based on insights, surface strategic discrepancies (like mismatched audience vs. active users), and collaborate closely with marketing and product to turn complex findings into clear actions.

My background in Civil Engineering strengthens how I approach complex problems, end-to-end data pipelines, and stakeholder-ready reporting. From automating reporting workflows with Excel (VBA/Power Query) and SQL to building Power BI KPI dashboards, I consistently focus on accuracy, clarity, and automation—whether in business intelligence work or projects like an AI-driven risk audit using Generative AI and LLM tooling.