Julian Urrego Ortiz
About Julian Urrego Ortiz
Julian Urrego Ortiz is an ML Infrastructure Engineer with a diverse background in data science and engineering. He has worked for several companies in Colombia, including Cementos Argos and Perficient Latin America, and holds multiple degrees in civil engineering and atmospheric sciences.
Current Role at Bearing
Julian Urrego Ortiz serves as an ML Infrastructure Engineer at Bearing since 2022. In this role, he focuses on developing and implementing machine learning infrastructure solutions. His work involves applying quantitative analysis and scientific programming to address industry challenges. Julian's expertise includes creating forecasting and prediction strategies that leverage both physics-driven and data-driven methodologies.
Previous Experience in Data Science and Engineering
Julian has a diverse background in data science and engineering. He worked as a Data Scientist at Perficient Latin America from 2021 to 2022. Prior to that, he served as a Data Analyst at Summan S.A.S for five months in 2019. His experience also includes a role as a Científico de datos at Cementos Argos from 2020 to 2021. Earlier in his career, he worked as a Design Engineer at Area Ingenieros Consultores S.A.S in Medellín, Colombia, from 2014 to 2015.
Educational Background in Engineering and Sciences
Julian holds a Master of Science in Atmospheric Sciences and Meteorology from Universidad de Antioquía, where he studied from 2016 to 2019. He also earned a Bachelor's degree in Civil Engineering from Universidad EAFIT, completing his studies from 2009 to 2014. Additionally, he obtained a Post-graduate diploma in Structural Engineering from Universidad EAFIT in 2015. His educational background provides a strong foundation for his work in engineering and data science.
Skills and Expertise in Data Analysis
Julian possesses strong skills in scientific programming, which he applies to solve various industry problems. His expertise includes implementing forecasting and prediction strategies, utilizing both physics-driven and data-driven approaches. He emphasizes quantitative analysis in his professional work, contributing to effective decision-making and problem-solving in his roles.
Interpersonal Skills and Team Collaboration
Recognized for his interpersonal skills, Julian enjoys sharing knowledge and collaborating with team members. His ability to work effectively in teams enhances project outcomes and fosters a positive work environment. His colleagues appreciate his contributions as a team player, which is essential in collaborative engineering and data science projects.