Eliud Meza
About Eliud Meza
Eliud Meza is a Data Scientist with a strong background in aerospace engineering and machine learning. He has worked at notable organizations such as NASA and NEORIS, contributing to various projects that improved predictive models and client satisfaction rates.
Work at NEORIS
Eliud Meza has been employed at NEORIS as a Data Scientist since 2019. In this role, he focuses on data analysis and machine learning applications. His contributions include increasing the precision of predictive models and developing innovative solutions to complex problems. Meza's work has significantly impacted the efficiency of operations within the organization.
Education and Expertise
Eliud Meza holds a Master of Science in Aerospace, Aeronautical and Astronautical/Space Engineering from ISAE-SUPAERO, which he completed between 2016 and 2018. Prior to this, he earned a degree in Aeronautical Engineering from Universidad Autónoma de Nuevo León, studying from 2008 to 2013. His educational background provides a strong foundation in engineering principles and data science methodologies.
Background
Eliud Meza began his professional career as an Aeromechanics Intern at NASA Ames Research Center in 2013, where he worked for six months. He then transitioned to a role as a Material Planner Engineer at VivaAerobus, serving from 2013 to 2016. Following this, he worked at ArianeGroup in business development and strategy for six months in 2018. His diverse experiences contribute to his expertise in data science and engineering.
Achievements
Eliud Meza has achieved notable results in his career, including a 6% increase in the precision of a machine learning predictive model for concrete services. He also contributed to a 15% volume increase for small clients through effective management of a dynamic overbooking model. Additionally, he developed an alternative model for detecting potential fuel thefts using anomaly detection techniques. His work has consistently focused on enhancing operational efficiency and client satisfaction.