• Bringing insights of Human Resources data (promotions, scores, demographics and so on)• Identifying patterns and trends to convert them into meaningful information or solutions to detected issues• Gathering data from existing data bases and processing it through Python using Pandas and Numpy’s libraries• Implementing analytics visualizations in Tableau and in Python, through Plotly using basic and statistical charts

I am about to submit a novel method that I have been researching and developing, for detecting the Earth's deformation using Machine Learning, to a specialized scientific journal.

Awarded with a scholarship to visit Tokyo in order to continue my research about detection of the Earth's deformation through Machine Learning

• Implementing several approaches to apply a semi-supervised ML algorithm to processed InSAR images data in order to detect the Earth's deformations. • Creating time series analysis to evaluate the accuracy of the predictions.

Developing a student dashboard based on learning analytics with data obtained from Moodle. • Data cleaning and processing in Python using Pandas. • Data management and storage using MongoDB Atlas. • UI design and creation with Figma and ReactJS.

Using a semi-supervised machine learning algorithm to detect Earth deformation after seismic movements.• As part of Dr. Aoki's Laboratory.• Cleaning and preparing the input data using Numpy and plot it making use of Pyplot from Matplotlib.• Translating the algorithm from MATLAB to Python.

Applying several Microsoft technologies such as .NET, Azure DevOps or PowerApps (Canvas and Model-Driven)