Hello! Welcome to my Data Science Project Portfolio

I started my career as a cinema attendant at the age of 16, I even became a waiter until I started college to be able to do an internship with Systems Implementation for various segments such as insurance companies, banks, telecommunications.
Currently, I carry out the parameterization of the clients' business rules in the tools of decision engines, such as credit policies, fraud, registration validation, etc.
At the same time, I keep myself daily in Data Science building personal projects to add strategies to be implemented in clients.
My goal is to take data-driven decisions in a more assertive and high-impact way for the client.

Projects

Insurance Health Cross Sell

Ordering by score of customers who are likely to purchase a new health insurance product.

Rossmann Sales Prediction

Consultation on Telegram of the sales forecast by store for the next six weeks.

Web Scraping for E-commerce

Data scraping in e-commerces to study the sale of new products

House Rocket Insights

Evaluate which portfolio homes the company should buy and how much to resell for.

Skills

Programming Languages and Database

  • Python for Data Analysis.
  • Webscrapping with Python
    (Beautiful Soup and Selenium)
  • SQL.
  • SQLite, MySQL, Postgres.

Software Engineering

  • Python Intermediate.
  • Ubuntu, VIM and Docker.
  • Git, Github, Cookiecutter and
    Virtual Enviroment (venv, poetry)
  • Flask, FastAPI, Django and Streamlit.
  • AWS Amazon, Google Cloud Plataform (GCP) and Heroku.

Statistics and Machine Learning

  • Descriptive Statistics.
  • Regression, Classification, Clustering and
    Learn to Rank.
  • Data balancing, Attribute selection and Dimensionality reduction.
  • Performance metrics: RMSE, MAE, MAPE, Confusion Matrix, Precision, Recall, Curve ROC.
  • Sklearn, Scipy.

Data Visualization

  • Matplotlib, Seaborn and Plotly.
  • Power BI.