Skip to content
View JFernandoAC's full-sized avatar

Block or report JFernandoAC

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Content in all repositories owned by your account will be closed.
Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
JFernandoAC/README.md

Hi there! 👋 I'm José Fernando Avila Camberos

I am a Data Analyst who turns raw, messy data into actionable insights and machine learning models. I work across the full cycle: cleaning and modeling data in SQL and Python, building and explaining predictive models, deploying them with Docker, and delivering results in dashboards. I also build AI agents that answer business questions in SQL.

🛠 Tech Stack & Skills

  • Data Analysis & Processing: Python, Pandas, NumPy, SQL, PostgreSQL
  • Machine Learning: scikit-learn, XGBoost, K-means, SHAP, MLflow
  • Data Visualization: Matplotlib, Seaborn, Plotly
  • Dashboards: Power BI (DAX, Power Query), Tableau, Streamlit
  • Deployment & Engineering: Docker, FastAPI, pytest, Git
  • AI Development: LangChain, LangGraph, AI Agents, Claude Code
  • Automation & Extraction: Web Scraping (BeautifulSoup, Requests), Scripting (openpyxl)

🚀 Featured Projects

🤖 Data Science & Machine Learning

  • Customer Churn Prediction & Segmentation Who are an online retailer's customers, and who is about to stop buying? Segmented 5,852 customers with RFM + K-means and predicted churn with XGBoost (ROC-AUC 0.76 on unseen customers), explained with SHAP. Includes MLflow tracking, a FastAPI model served with Docker, and a 4-page Power BI dashboard on PostgreSQL.

🧠 AI Development

  • Text-to-SQL Agent AI Agent that converts natural language to SQL queries using LangChain, Google AI Studio (Gemini), and FastAPI.

📊 Data Analysis

  • Mexico City Airbnb Analysis End-to-end analysis of 29,329 Airbnb listings in Mexico City: data cleaning in Python, business questions answered in SQL, and results delivered as a Power BI report and an interactive Streamlit app.

🎓 Certifications

📫 Let's Connect

Pinned Loading

  1. text-to-sql-agent text-to-sql-agent Public

    AI Agent that converts natural language to SQL queries using LangChain, Google AI Studio (Gemini), and FastAPI.

    Python

  2. mexico-city-airbnb-analysis mexico-city-airbnb-analysis Public

    End-to-end analysis of 29,329 Airbnb listings in Mexico City: data cleaning in Python, business questions answered in SQL, and results delivered as a Power BI report and an interactive Streamlit app.

    Python

  3. customer-churn-segmentation customer-churn-segmentation Public

    Customer churn prediction and segmentation for an online retailer: RFM + K-means segments, XGBoost churn model explained with SHAP, MLflow tracking, FastAPI + Docker API and a Power BI dashboard on…

    Jupyter Notebook