Software Engineer turned Data Engineer & Data Scientist. Master's in Data Science & Business Analytics @ IMMUNE Technology Institute 🇪🇸 Building end-to-end data pipelines and ML systems that solve real business problems. 📍 Colombia · 🌍 Open to remote & relocation · 🗣️ Spanish (native) · English (B2)
Full-lifecycle MLOps system for credit default risk scoring: Glue ETL → SageMaker Pipelines (training, governance, Model Registry) → dual deployment (native SageMaker Endpoint + FastAPI/Docker/ECS Fargate/API Gateway) → A/B tested (10/10 prediction match) → drift monitoring (validated against real simulated drift, z-score 6.67) → automated retraining via Lambda + EventBridge. Entire infrastructure defined as code with Terraform; CI/CD with GitHub Actions.
AWS Terraform SageMaker Docker FastAPI ECS Fargate API Gateway Lambda EventBridge GitHub Actions XGBoost
🔗 credit-risk-mlops — production pipeline 🔗 credit-risk-eda — exploratory analysis & modeling
End-to-end streaming pipeline processing 6.3M financial transactions in real time.
Detects fraud in milliseconds using GBT model deployed with MLflow on Azure.
Azure Databricks Spark Structured Streaming Event Hubs Delta Lake MLflow CosmosDB Key Vault PySpark
🔗 fraud-detection-azure-databricks
Physics-first two-engine solution for horizontal-well geology prediction, achieving an 8x RMSE reduction through structural dip modeling combined with constrained gamma-ray DTW alignment.
Python Data Science Time Series Signal Processing Kaggle
🔗 rogii-wellbore-geology-prediction
ML model identifying 2,119 high-risk customers representing $1.9M annual revenue at risk.
Full pipeline: EDA → Feature Engineering → Random Forest → Executive Report.
Python Scikit-learn Random Forest Pandas Matplotlib Seaborn Google Colab
🔗 churn-prediction-telecom
RFM + K-Means clustering to identify distinct customer groups and purchasing patterns.
Strategic recommendations for marketing and retention teams.
Python K-Means RFM Analysis Pandas Seaborn
🔗 Customer-Segmentation-Analysis-for-an-E-commerce-Platform
| Área | Tecnologías |
|---|---|
| ☁️ Cloud & Big Data | AWS (Glue, SageMaker, ECS Fargate, Lambda, API Gateway, EventBridge) · Azure Databricks · ADLS Gen2 · Event Hubs · CosmosDB · Spark · Hadoop |
| 🤖 Machine Learning | Scikit-learn · XGBoost · MLflow · Random Forest · GBT · K-Means · RFM |
| 🏗️ MLOps & IaC | Terraform · Docker · SageMaker Pipelines & Model Registry · GitHub Actions (CI/CD) |
| 💻 Lenguajes | Python · SQL · JavaScript · R |
| 📊 Visualización | Power BI · Matplotlib · Seaborn |
| ⚙️ Backend & DevOps | FastAPI · Django · Docker · Jenkins · Node.js |
| 🗄️ Bases de datos | SQL Server · NoSQL · Supabase · SSIS |
Master's in Data Science & Business Analytics IMMUNE Technology Institute, Spain — 2025–2026
IA · Cloud Computing · Machine Learning · Deep Learning · Power BI · Big Data Degree in Software Engineering Universidad Politécnica Territorial Agro Industrial del Táchira — 2019–2024 Web Dev · Mobile · Servers · SQL · NoSQL · Docker · AWS · Python
- 🏅 AWS Business Intelligence Engineer — Udacity
- 🏅 Python & Mathematics for Data Science — Platzi
- 🏅 Statistical Mathematics, Probability & Linear Algebra — Platzi
- 🏅 Power BI — Platzi
- 🏅 Web Development — LexpinOnline
