Camilo Mocetón
About Camilo Mocetón
Camilo Mocetón is an experienced data scientist specializing in trend analysis within the retail sector, utilizing machine learning for client and store profiling. He has worked at NEORIS since 2021 and previously spent eight years at Nielsen, focusing on client segmentation and data integrity.
Work at NEORIS
Camilo Mocetón has been employed at NEORIS as a Data Scientist Experienced since 2021. In this role, he focuses on analyzing trends in mass consumption categories within the retail sector. His work involves utilizing machine learning models to profile and classify retail stores and clients, contributing to data-driven decision-making processes within the organization.
Education and Expertise
Camilo Mocetón is currently pursuing a Magister en Estadística at Universidad Nacional de Colombia, a program he has been involved with since 2017. He previously earned a degree in Estadístico from the same institution, completing his studies from 2008 to 2012. His educational background provides a strong foundation in statistical analysis and data science methodologies.
Background
Before joining NEORIS, Camilo Mocetón worked at Nielsen as a Data Scientist for eight years, from 2013 to 2021. During his tenure at Nielsen, he implemented client segmentation strategies using machine learning to analyze behavior patterns related to payment and order generation. His experience in the retail sector has equipped him with valuable insights into consumer behavior.
Achievements in Data Science
Camilo Mocetón has developed a machine learning model aimed at predicting employee attrition. This model analyzes various factors contributing to employee turnover, showcasing his ability to apply data science techniques to real-world problems. Additionally, he created quality assurance processes for databases, ensuring data integrity and reliability for analysis.