Biomedical Engineer turned Data Scientist, with 5+ years building end-to-end data solutions in healthcare analytics, business intelligence, and AI automation.
I work at the intersection of machine learning, automation and health systems — from predictive models and LLM agents to strategic dashboards and clinical pipelines. Currently completing a Master's in Data Science at EAFIT, with a thesis on NLP/ML for healthcare complaint prediction using BETO and XGBoost.
🏥 Healthcare Analytics → RIPS, PQRS, tutelas, clinical cohorts, EPS operations
🤖 ML / AI → NLP, Computer Vision, LLM Agents, RAG
📊 Business Intelligence → Power BI, Tableau, advanced DAX, data storytelling
⚙️ Automation → n8n, Python ETL, GCP, REST APIs
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🤖 Machine Learning & Deep Learning
📊 Business Intelligence
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🏥 Healthcare & Clinical Analytics
⚙️ Data Engineering & Cloud
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Languages
ML / AI
BI & Visualization
Infrastructure
Recognizing bird species by adding a synthetic UV channel and extracting vision embeddings with BEiT — simulating tetrachromatic avian perception.
Results: Accurate UV simulation · Embeddings → UMAP → species clustering · Full pipeline: cleaning → normalization → feature extraction
Autonomous agent systems for process automation — conversational agents, text classification, appointment management, and API integration.
AI agent that generates personalized training plans for running, cycling and triathlon with dynamic load recommendations, zone targets, and fatigue adjustments.
Advanced computer vision and ML projects: HOG, SVM, clustering, colorimetry, and image normalization pipelines.
Interactive BI portfolio with dashboards in Power BI, Tableau and Looker, automated ETL, risk models, PQRS analytics, and clinical cohort analysis.
