I am a Master's student of Information Engineering and I am currently working on my thesis project focused on helping you to interact and interpret Machine Learning systems. I have implemented data analytics and Big Data solutions in contexts suchs as tax administration, public health and mobility. In addition, I have previous experience in software development (backend and frontend) and TI infraestructure.
December 2018 - To Date
We help companies to extract insights from data for effective decision-making through machine learning algorithms and interactive visualizations. We use agile methodologies for continuos stakeholder involvement and quick value generation.
January 2017 - December 2018
December 2017 - April 2018
Teaching activities for the Big Data and Data Analytics course: Data science, information visualization and Machine Learning modules. Development of theoretical and practical sessions with a total duration of 60 hours.
April 2016 - June 2017
Software development and support for electronic payment systems. Most pf the time I focused in the design and development of the frontend layer applying AngularJs and REST webservices.
November 2014 - April 2016
Management and implementation of projects of virtualization and information security. More specifically, I worked in the administration of VMware virtualization environments, application and database server diagnostic and implementation of domain controller and terminal server hostings.
July 2014 - November 2014
June 2012 - October 2013
Requirement analysis and software development based on Java Enterprise Edition, Vaadin, Oracle and IBM WebSphere Application Server.
January 2017 - To Date
Master of Information Engineering with enphasis in Machine Learning and Visual Analytics.
February 2008 - December 2015
Systems Engineering with enphasis in software development, databases and Artificial Intelligence.
I can help you to take advantage of data by implementing statistical and machine learning models for more effective decision-making.
My experience involves different stages of data lifecycle: getting and transforming large amounts of data and creating interactive data visualizations for insights extraction.
For delivering data to staff and customers, you will need a robust and innovative software system applying agile development and cloud deployment common practices.