Pau Labarta Bajo
About Pau Labarta Bajo
Pau Labarta Bajo is a Machine Learning Engineer and Founding Talent Member at Braintrust, where he has worked since 2020. He holds advanced degrees in Mathematics and Quantitative Economics and has a diverse background in machine learning, data science, and financial modeling.
Work at Braintrust
Pau Labarta Bajo has been a Machine Learning Engineer and Founding Talent Member at Braintrust since 2020. In this role, he contributes to the development and implementation of machine learning solutions, leveraging his extensive background in mathematics and data science. His work at Braintrust involves tackling complex problems and enhancing the platform's capabilities through innovative machine learning approaches.
Education and Expertise
Pau Labarta Bajo holds multiple degrees in mathematics and quantitative economics. He earned a Bachelor's and Master's degree in Mathematics from Universitat Politècnica de Catalunya from 2005 to 2010. He furthered his education with a Master's degree in Wirtschaftsmathematik from Bielefeld University in 2011. Additionally, he completed a Master's degree in Quantitative Economics and Finance at Università Ca' Foscari Venezia in 2012. His strong academic foundation supports his expertise in machine learning and data science.
Background
Pau Labarta Bajo has a diverse professional background in data science and machine learning. He has worked in various roles, including Data Engineer at Speak for one month in 2020, and as a Machine Learning Engineer at EasyHealth from 2021 to 2022. His experience also includes positions at Cogsy as a Time Series ML Engineer and as a Data Scientist at cyngn. His work spans multiple industries, addressing problems such as financial derivative pricing and demand prediction for online shopping.
Achievements
Pau Labarta Bajo has developed deep learning models for art generation, showcasing his ability to blend technical skills with creativity. He possesses strong coding skills in Python, essential for building and deploying machine learning solutions. His passion for transforming ideas into models and subsequently into APIs/products highlights his commitment to the full lifecycle of machine learning product development.