Juan Pablo Rocha Amado

Juan Pablo Rocha Amado has a diverse work experience in the field of data engineering and software development. Juan Pablo is currently working as a Data Engineer at Leniolabs_ LLC since December 2020. Prior to this, they worked as a Big Data Architect at Globant from June 2019 to November 2020.

Before joining Globant, Juan Pablo worked at General Motors for several roles. Juan Pablo was a Big Data Developer from April 2017 to April 2018, where they integrated data from different systems using Hadoop, Datastage, and Teradata, and also developed software using Java, Python, and shell script. Juan Pablo then transitioned to a BI Technical Analyst role from November 2013 to March 2017, where they had responsibilities related to BI finance applications, IBM Cognos, Tableau, Microstrategy, MS Analysis Services BI reporting technologies, and advanced analytics technologies like SAS, SPSS, and IBM Watson.

Juan Pablo's earlier experience includes working as an IT Compliance Analyst at General Motors from February 2013 to October 2013, a Svc Info Developer I at HP Enterprise Services from February 2012 to February 2013, and a Freelancer - Software Developer at ITX Corp. from February 2008 to February 2012. Juan Pablo also had an internship as a Software Analyst at COA Consultora S.A. from April 2007 to November 2007 and worked as a Software Developer at Recursos Tecnológicos SRL from September 2005 to April 2007.

Juan Pablo Rocha Amado has a diverse education history in the field of engineering and data analysis. Juan Pablo obtained a Bachelor of Engineering degree in Information Technology from Pontificia Universidad Católica Argentina 'Santa María de los Buenos Aires' in 2010. In 2012, they pursued a Master of Engineering degree in Knowledge Discovery and Data Mining from Universidad Austral, Buenos Aires.

In addition to their formal education, Juan Pablo Rocha Amado has also obtained several certifications in the field. In 2017, they became a SAS Certified Base Programmer for SAS 9. Juan Pablo further enhanced their knowledge by completing various online courses, including "Deep Learning Specialization," "Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization," "Structuring Machine Learning Projects," "Data Scientist with Python Track," "Machine Learning," and "Neural Networks and Deep Learning" from institutions such as Coursera and DataCamp. These certifications and courses highlight their dedication to continuously expanding their skills and knowledge in data analysis and machine learning.