Oscar Eduardo Luna Nieves

Oscar Eduardo Luna Nieves has been working in the field of data science since 2014. Oscar Eduardo started as a Research Assistant at UNAM - CCADET, where they developed an intelligent system to predict the 10-year life survival of women diagnosed with breast cancer and implemented a genetic algorithm to create drum rhythms. In 2016, they began working as a Data Scientist at ENOVA Mexico, where they carried out descriptive and inferential analyzes of the academic performance of students, teachers and educational centers and created regression models to try to explain the relationship between certain characteristics of learning objects and grades. In 2018, they moved to Grupo Cinco M as a Data Scientist, where they were responsible for data ingestion, cleaning, storage, analysis and visualizations. Oscar Eduardo also created an LDA model (Latent Dirichlet Allocation) on a set of more than 35 thousand articles from 5 different websites, using web scraping in order to extract topics and create content-based clusters to build a taxonomy on a DMP and capture users content preferences. Currently, Oscar is working as a Machine Learning Engineer at IDmission since 2019.

Oscar Eduardo Luna Nieves obtained a Masters in Computer Science from the Universidad Nacional Autónoma de México in 2017, specializing in Artificial Intelligence. Oscar Eduardo also obtained a Computer Engineering degree from the same university in 2010, specializing in Embedded Systems. Oscar Eduardo has also obtained three certifications from Coursera, namely 'Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization' (2019), 'Structuring Machine Learning Projects' (2019), and 'Neural Networks and Deep Learning' (2019).