I like solving problems and getting ideas off paper and programming. I have experience with scientific methodology, software development, data analysis in retail, HR (people analytics) and credit.
I currently work at agibank in the modeling area, building propensity and recommendation models. Using scientific methodologies, exploratory analysis, visualization and data mining through tools such as: R, sagemaker, Jenkins and AWS. He actively participates in the kaggle platform with some analyzes and predictions and takes numerous courses in various areas.
Interested in the areas of: machine learning, algorithms, big data and data science.
- Recommender Systems for Article Comments: Analysis in Kaggle
- Data Scientist or Data Analyst? What's the difference? Challenge of datahackers Analysis in Kaggle e 4th Place Competition Announcement (live)
- Store Sales Forecasting ARIMA and AUTOARIMA: Analysis in Kaggle
- Association Rules Mining/Market Basket Analysis: Analysis in Kaggle
- RFM Segmentation and Customer Analysis: Analysis in Kaggle
- Prediction of Credit Risk using RandomForest: Github Repository
- Employee turnonvoer risk prediction for HR (People Analytics) using RandomForest: Github Repository
- Deploying Logistic Regression Model to Predict Kaggle's Titanic Disaster: Github Repository