Marjolaine Grunenberger
About Marjolaine Grunenberger
Marjolaine Grunenberger is a Data Engineer with a strong educational background in mathematics and machine learning. She has worked in various roles, including as a Data Scientist and Mathematics Tutor, and currently works at Doctrine in Paris.
Work at Doctrine
Marjolaine Grunenberger has been employed at Doctrine as a Data Engineer since 2021. In this role, she applies her expertise in data analysis and engineering to support various projects within the organization. Her work involves utilizing advanced data processing techniques to enhance the company's data-driven decision-making capabilities.
Education and Expertise
Marjolaine Grunenberger has a strong educational background in mathematics and data science. She studied at Université Paris Dauphine - PSL, where she completed a MASH Master focusing on Mathematics, Machine Learning, and Bayesian Statistics from 2017 to 2018. Additionally, she earned a Master 1 in Applied Mathematics and Statistics at the same institution from 2016 to 2017. She also studied at École normale supérieure Paris-Saclay, achieving an MVA Master in Machine Learning and Applied Mathematics from 2017 to 2018, and holds a Bachelor's degree in Mathematics, Statistics, and Computer Science from the University of Warwick, completed in 2016.
Previous Experience as Data Scientist
Before joining Doctrine, Marjolaine Grunenberger worked as a Data Scientist at Explain from 2018 to 2020. During her two years in this role, she focused on data analysis and modeling, contributing to various projects aimed at leveraging data insights for business applications. Her experience in this position helped her develop practical skills in data science methodologies.
Tutoring Experience at Université Paris Dauphine
Marjolaine Grunenberger served as a Mathematics Tutor at Université Paris Dauphine from 2016 to 2018. In this capacity, she provided academic support to students, helping them understand complex mathematical concepts and improve their problem-solving skills. This role allowed her to share her knowledge and foster a deeper appreciation for mathematics among her peers.