Pauline Romagon
About Pauline Romagon
Pauline Romagon is a Senior Data Scientist with extensive experience in data analysis and machine learning, currently working at Sia Partners and Enedis in Lyon, France. She specializes in preprocessing unstructured data, sentiment analysis, and natural language processing.
Current Role at Sia Partners
Pauline Romagon has been serving as a Senior Data Scientist at Sia Partners since 2021. In this role, she focuses on developing innovative machine learning models and techniques. Her expertise in data science allows her to contribute effectively to various projects within the organization. She is based in Lyon, Auvergne-Rhône-Alpes, France.
Experience at Enedis
Since 2020, Pauline Romagon has worked as a Data Scientist at Enedis. In this position, she has been involved in data analysis and processing, specifically focusing on unstructured data and textual data analysis. Her work contributes to the company's efforts in leveraging data for operational improvements.
Professional Background
Pauline Romagon has a diverse professional background in data science. She previously worked at EY as a Senior Data Scientist from 2019 to 2021 and as a Consultante Data Scientist from 2018 to 2019. Additionally, she held the position of Responsable partenariats culturels at the Association des Élèves de l'Ecole Centrale de Lyon from 2016 to 2017. Her early career included roles at LVMH and BMI SYSTEM.
Educational Qualifications
Pauline Romagon holds a Master of Science in Ingénieure généraliste from Ecole Centrale de Lyon, where she studied from 2015 to 2018. She also completed an Honours Bachelor of Science in Computer Science with a Data Science Option at Université d'Ottawa in 2018. Prior to that, she attended Classes préparatoires Lycée Blaise Pascal, focusing on MPSI - MP * from 2013 to 2015.
Specialization and Expertise
Pauline Romagon specializes in preprocessing and exploration of unstructured data, with a strong focus on sentiment analysis and natural language processing (NLP). Her expertise in these areas enables her to analyze complex data sets and derive meaningful insights, contributing to advancements in data-driven decision-making.