Raphael Sourty
About Raphael Sourty
Raphael Sourty is a Data Scientist at ManoMano in Paris, France, with a strong background in data science and deep learning. He holds a PhD in Deep Learning and NLP from Université Paul Sabatier Toulouse III and has contributed to various internships and projects in the field.
Work at ManoMano
Raphael Sourty has been employed as a Data Scientist at ManoMano since 2022. He operates from the company's office located in Paris, Île-de-France, France. In this role, he focuses on leveraging data to enhance decision-making processes within the organization.
Previous Experience in Data Science
Prior to his current position, Raphael Sourty gained valuable experience through various internships. He worked at TELEGRAFIK as a Data Science intern for four months in 2017. He then completed a one-year internship at SIGFOX from 2018 to 2019. Additionally, he interned at McGill University in 2018 for three months. His early career included a two-month internship as a Statistician at MAAF Assurances in 2016.
Education and Expertise
Raphael Sourty holds a DUT STID from Université de Poitiers, where he studied Business Intelligence from 2014 to 2016. He furthered his education at Université Paul Sabatier Toulouse III, earning a Licence in Data Science in 2017, followed by a Master's degree in Engineering in Data Science from 2017 to 2019. He completed his PhD in Deep Learning and NLP at the same university from 2019 to 2023. His academic focus includes information retrieval and knowledge bases.
Research and Contributions
During his PhD, Raphael Sourty specialized in Deep Learning, Natural Language Processing, and Knowledge Bases. He has contributed to open source projects, demonstrating his expertise in Python and machine learning. His work emphasizes enhancing data-driven decision-making processes.
Achievements in Data Science
Raphael Sourty has achieved Kaggle Expert status, indicating his proficiency in data science competitions. This recognition reflects his skills and knowledge in the field, further establishing his credibility as a data scientist.