✨ Working with data, technology and in project environments since 2003.
📚 Post graduate Data Scientist, Lean Six Sigma Black Belt, Project Management Professional (PMP), Bachelor in Business Administration.
🛠 Been around the block: Worked in many different sectors, such as Retail, Telecom, IT, Manufacturing, Agriculture, Construction, Real State, Consultancy and Energy, among others.
🎯 Goals: Discover valuable insights using data science and technology in project environments to improve business processes.
💻 Passionate about technology and data, fast learner and energetic.
🤝I love a good challenge as well as the opportunity to learn and help others.
🔭 I’m currently working on a clustering project to manage over 5.000 SKUs with over 200 features each from 10 different factories.
🌱 I’m currently learning neural networks, AI automations and advanced data visualization.
👯 I’m looking to collaborate on Machine Learning, AI and automation projects.
👨💻 All of my projects are available at My Portfolio.
📝 I write articles on LinkedIn.
💬 Ask me about business analytics, data extraction, manipulation, modelling and visualization, process improvement and project management.
📄 Know about my experiences here.
⚡ Fun fact about me: I try to always be on the sweet spot below:
⚡ Another fun fact about me: my nickname comes from me having big feet since I was a teenager (size 13 US, 47 EU, 12 UK) and the release of movie Godzilla (1998).
Python, Jupyter, Pandas, Numpy, Scikit-Learn, Matplotlib, Seaborn, PyTorch, TensorFlow, Streamlit, Beautiful Soup, Spacy, NLTK, Transformers, Keras, PowerBI, Power Automate, Power Apps, Excel, Minitab, VSCode, MySQL, SQL Server, Anaconda, CSS, HTML.
| Project Name | Short Description | Link to Project | Programming Languages |
|---|---|---|---|
| Data Science Project Assistant | Automates the creation of a data science tutorial with machine learning using AI Agents, Serper API and OpenAI. | DS Project Assistant | Python, CrewAI, Open_AI API, Serper API |
| COVID19-LATAM | Analysis of COVID-19 vaccination in Latin America to assess its impact on case numbers and deaths. | COVID-19 Latam | SQL, Tableau, Python |
| Interconnect | Predicts customer churn for a telecom company by analyzing user contracts and services. | Interconnect | Python, pandas, scikit-learn, numpy, matplotlib, seaborn, LightGBM, CatBoost, XGBoost |
| Junky-Union | Sentiment analysis project to classify movie reviews as positive or negative. | Junky-Union | Python, NLTK, spacy, BERT, scikit-learn, numpy, matplotlib, seaborn, math, LightGBM, CatBoost, XGBoost |
| Drone-Delivery | Drone delivery route optimization by analyzing city coordinates and shipment volumes. Identifies the best location for a warehouse. | Drone-Delivery | Python, pandas, vector calculations |
| Loyalty-Savings | A predictive model to estimate additional profits from two loyalty programs at a major retailer. | Loyalty-Savings | Data Analysis, Excel, Regression |
| MNSC | A model to analyze and track the profitability of contracts at a law firm. | MNSC | Business Analytics, Excel, Data Modelling, Dashboards |
| Crazy-Taxi | Predicting taxi demand during rush hours using time series analysis. | Crazy-Taxi | Python, pandas, scikit-learn, numpy, motplotlib, LightGBM, CatBoost, XGBoost |
| Rusty-Bargain | Predicting the market value of used cars using different machine learning models. | Rusty-Bargain | Python, pandas, scikit-learn, numpy, matplotlib, seaborn, math, time, LightGBM, CatBoost, XGBoost |
| Insurance | Predicting the number of insurance claims and identifying potential risks. | Insurance | Python, pandas, scikit-learn, numpy, seaborn, K-Neighbours |
| Oily-Giant | Analyzing the best locations for oil well development based on potential profit margins. | Oily Giant | Python, pandas, scikit-learn, numpy, matplotlib, scipy |
| Beta-Bank | Predicting customer churn to improve retention strategies for a financial institution. | Beta-Bank | Python, pandas, scikit-learn, matplotlib |
| Megaline-Classification | Classifying users into appropriate plans based on usage patterns for a telecom provider. | Megaline Classification | Python, pandas, scikit-learn |
| Zuber | Data analysis on ride-sharing service trends and competitor evaluation. | Zuber | Python, pandas, numpy, Beautiful Soup, matplotlib, scipy |
| Videogames | Market analysis of video game platforms and genres for business insights. | Videogames | Python, pandas, numpy, matplotlib, seaborn, scipy |
| Vehicles | Predictive model for vehicle data to analyze various attributes and their impact on price. | Vehicles | Python, pandas, scikit-learn, plotly express, streamlit |
| Megaline | Analysis of telecom user behavior to improve product offerings and customer segmentation. | Megaline | Python, pandas, scikit-learn, numpy, math |
| Instacart | Analyzing grocery shopping patterns to optimize product placements and marketing strategies. | Instacart | Python, pandas, numpy, matplotlib |