Sebastián Villalobos Alva

Operations Associate @ ScaleAI

About Sebastián Villalobos Alva

Sebastián Villalobos Alva is an Operations Associate at Scale AI, specializing in machine learning and data science. He holds a Bachelor's degree in Mechatronics, Robotics, and Automation Engineering from Universidad Iberoamericana and a MicroMasters in Statistics and Data Science from MITx.

Work at ScaleAI

Sebastián Villalobos Alva serves as an Operations Associate at Scale AI, a position he has held since 2021. He is based in the Mexico City Metropolitan Area. In this role, he contributes to the operational efficiency of the company, leveraging his background in data science and machine learning. His work includes developing applications that enhance classification accuracy and streamline processes.

Education and Expertise

Sebastián holds a Bachelor of Engineering in Mechatronics, Robotics, and Automation Engineering from Universidad Iberoamericana, Ciudad de México, where he studied from 2015 to 2021. He furthered his education by completing the MITx MicroMasters® in Statistics and Data Science through edX from 2021 to 2022. His academic background provides a strong foundation in engineering principles and advanced data analysis techniques.

Background

Before joining Scale AI, Sebastián worked as a Programming Intern at Universidad Iberoamericana, Ciudad de México from 2020 to 2021. During this internship, he gained practical experience in programming and data analysis, which contributed to his skill set in machine learning and application development.

Achievements in Machine Learning

Sebastián developed a Python web application that utilizes Natural Language Processing and Support Vector Machine techniques. This application efficiently classifies press releases related to megaprojects and indigenous Mexican communities. His work has resulted in a significant reduction in the number of press releases needing review by 90-93%, demonstrating his expertise in applying advanced machine learning techniques to real-world problems.

Classification Accuracy in Applications

The application developed by Sebastián maintains an overall classification accuracy rate of 85-90%. This high level of accuracy showcases his proficiency in machine learning and data science, highlighting his ability to create effective solutions for complex classification tasks.

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