Senior Data Scientist @ Thermo Fisher Scientific · PhD in Electrical Engineering · Adjunct Professor @ ITESO
I'm a data scientist and university educator based in Guadalajara, Mexico. My path spans automatic control, applied machine learning, and AI engineering—from researching robust control systems to building data products, generative AI applications, and reproducible ML workflows.
I enjoy turning complex technical ideas into useful products and hands-on learning experiences.
También hablo español. Me interesa construir sistemas de datos útiles, reproducibles y fáciles de comprender.
- 🧠 End-to-end machine learning systems, from experimentation to APIs, interfaces, and deployment.
- 🤖 Generative AI applications using RAG, NLP, vector search, and AI agents.
- 🎯 Recommender systems, computer vision, and applied predictive modeling.
- ⚙️ MLOps practices for reproducibility, orchestration, experiment tracking, and operation.
- 🎓 Practical data science education, technical mentorship, and curriculum design.
- 🧬 Senior Data Scientist at Thermo Fisher Scientific, working at the intersection of data, machine learning, and AI.
- 👨🏫 Adjunct Professor at ITESO, teaching undergraduate data science, data engineering, and production-oriented ML.
- 🎓 PhD and MSc in Electrical Engineering (Automatic Control) from CINVESTAV-IPN.
- ⚡ Control Engineering graduate from Universidad Nacional de Colombia.
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📚 Proyecto en Ciencia de Datos — Otoño 2026 — An active university course that guides students from development fundamentals to MLOps, deployment, and operation through reproducible, project-based learning.
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🚕 NYC Taxi Predictions — An end-to-end machine learning case study using XGBoost, MLflow, FastAPI, Streamlit, Prefect, and Docker Compose.
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🛡️ MLOps Bootcamp — Fraud Detection — A fraud-detection workflow covering exploratory analysis, feature engineering, model comparison, artifact serialization, and API-based inference.
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🤖 LLM Zoomcamp — Applied learning work around retrieval-augmented generation, vector search, Elasticsearch, model evaluation, and local LLMs.
- 🐍 Data & ML: Python, SQL, pandas, scikit-learn, XGBoost, TensorFlow
- ✨ AI & LLMs: LlamaIndex, LangChain, Hugging Face, RAG, vector databases, Elasticsearch
- 📦 Applications & MLOps: FastAPI, Streamlit, MLflow, Prefect, Docker, AWS, GCP
- 🔧 Engineering: Git/GitHub, PostgreSQL, Jupyter, Ruff, uv
- 🏁 Long-distance triathlon: endurance training, 70.3, and Ironman challenges.
- 🚴 Cycling tech: aerodynamics, bike fitting, race-day hydration, and fine-tuning my Cervélo P5.
- 🏋️ Strength training: balancing endurance work with barbell and dumbbell sessions.
- 🎧 Curiosity-driven podcasts: science, history, technology, culture, and the occasional unexpected rabbit hole.
I'm interested in conversations and collaborations around applied MLOps, AI-enabled learning, and data science education.