Gabriel Gonçalves Mota
About Gabriel Gonçalves Mota
Gabriel Gonçalves Mota is a Data Scientist with expertise in machine learning techniques and multivariate analysis. He has worked in various roles across multiple organizations, including D'Ieteren and Impaqtr, and holds degrees in Statistics from several universities.
Work at D’Ieteren
Gabriel Gonçalves Mota has been employed as a Data Scientist at D'Ieteren since 2021. His role involves applying advanced data analysis techniques to support the company's objectives. The position is based in Belgium, where he has continued to develop his expertise in data science and machine learning.
Education and Expertise
Gabriel holds a Master's degree in Statistics from Université libre de Bruxelles, completed between 2013 and 2015. He also earned a Bachelor's degree in Statistics from Universidade de Brasília, which he completed from 2007 to 2012. Additionally, he participated in an exchange program at Université Laval, studying Statistics from 2010 to 2011. His expertise includes Multivariate Analysis, Machine Learning techniques, and a strong interest in Bayesian Statistics.
Background
Gabriel began his career as an intern at GSK in Belgium, where he worked for two months in 2015. He then served as a Data Scientist at Figures to Facts from 2015 to 2017 and at Impaqtr from 2017 to 2021. Prior to these roles, he worked as a Statistical Consultant at Centro de Seleção e de Promoção de Eventos in Brasília from 2011 to 2012.
Achievements
Throughout his career, Gabriel has developed skills in various machine learning techniques, including Decision Trees, Neural Networks, and Genetic Algorithms. He has demonstrated proficiency in Multivariate Analysis methods such as Clustering, Principal Component Analysis, and Linear Discriminant Analysis. His ability to manage multiple tasks effectively is supported by results from a Talentoday personality test.
Personality and Interests
Gabriel identifies as an INTJ personality type according to the Myers-Briggs Type Indicator. He has a strong interest in Bayesian Statistics and the Design and Analysis of Experiments, reflecting his analytical mindset and commitment to advancing his knowledge in the field of data science.