👋 About Me

I’m Daniel Zambrano a Data Scientist who takes AI from notebooks to production. I build end-to-end solutions: ETL/ELT, ML/DL modeling, rigorous evaluation, and lightweight MLOps, always with security and governance in mind. I turn large, messy datasets into clear, deployable products and communicate results with crisp dashboards and documentation. I thrive in cross-functional teams and focus on impact: better decisions, lower risk, and visible ROI.

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🚀 Skills

 class Skill:
 	user = 'Daniel Zambrano'
	skills = [
  "🐍 Python (NumPy, pandas, scikit-learn, XGBoost, TensorFlow), SQL, Git",
  "🔬 EDA & feature engineering; supervised/unsupervised; time series",
  "🎯 Model evaluation & tuning (ROC-AUC, F1, RMSE, MAPE; Grid/Random/Bayes)",
  "⚙️ ETL/ELT & orchestration (Airflow/Prefect), dbt, Parquet",
  "🚀 APIs & deployment (FastAPI/Flask, Docker, PostgreSQL)",
  "📊 Data visualization & dashboards (Plotly, Power BI, Tableau)",
  "🔐 Security, privacy & explainability (governance, SHAP/LIME)",
  "🧭 Product mindset: problem framing, KPIs, ROI, stakeholder communication"]

	def getCity():
		return "Quito, Ecuador"
	
	def education():
       return [
            "Master’s in Data Science & Machine Learning — Artificial Intelligence",
            "Bachelor’s degree in Mechatronics Engineering."]

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🛠️ Tech Stack

📚 Languages

🤖 Data Science & Machine Learning

Also: XGBoost, LightGBM, CatBoost, statsmodels

⚡ Web & APIs

• ETL/ELT & Orchestration: Airflow, Prefect, dbt · Data formats: Parquet

🗄️ Databases & Caching

🚀 DevOps & Infra

📊 Data Visualization & Dashboards

🔐 Security, Privacy & Explainability

Governance · Model risk · SHAP / LIME

🤖🔩 Hardware & Robotics

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💼 Experience

Data Scientist — Spatium Robotics (2023–Present)

• I deliver end-to-end AI solutions: ETL/ELT pipelines, ML/DL modeling, rigorous evaluation, and lightweight MLOps. I productionize models via Dockerized REST APIs with PostgreSQL and communicate insights through interactive dashboards, always with security in mind.

Computer Vision Research Engineer — Spatium Robotics (2020–2023)

• Built real-time detection and tracking pipelines combining classic vision methods with modern deep learning (TensorFlow, OpenCV, YOLO, MobileNet). Led dataset curation/labeling and deployment on resource-constrained devices.

Robotics Developer — Spatium Robotics (2018–2020)

• Developed intelligent embedded systems integrating control and software; improved autonomous behavior with unsupervised learning; implemented sensor fusion and navigation/avoidance algorithms.

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🌟 Featured Projects

Project	What it does	Stack	Links
Early Detection of Autoimmune Diseases	Reproducible clinical ML pipeline for early signal detection (research support; not medical advice). Includes EDA, imputation, class balancing, cross-validated models, and SHAP explanations.		Repo Case Study Demo
Measuring & Mitigating Cognitive Debt from AI Use	Learning analytics to measure “cognitive debt” from AI assistance and generate action cards with LLMs. Dashboards, experiments, retention metrics, and guidance to reduce over-reliance.		Repo Case Study Demo
Crowd Density Estimation via Computer Vision	Real-time crowd flow and density maps with privacy-by-design (no identification). Lightweight tracking/detection and edge-friendly inference.		Repo Case Study Demo

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📊 GitHub Analytics

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🤝 Let’s collaborate

Got a data problem worth productizing? Let’s collaborate on ETL/ELT → ML/DL → MLOps, with rigorous evaluation, SHAP/LIME explainability, and privacy-first deployment.

“Let’s work together”

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