Thomas Lysensoone
About Thomas Lysensoone
Thomas Lysensoone is a data scientist based in Lille, Hauts-de-France, France, currently working at Jellysmack since 2018. He specializes in data-driven sports betting and has a background in applied mathematics and machine learning.
Work at Jellysmack
Thomas Lysensoone has been employed at Jellysmack as a Data Scientist since 2018. His role involves applying data science techniques to enhance the company's operations and strategies. Prior to his current position, he served as a Data Scientist Intern at Jellysmack for five months in 2018. His experience at Jellysmack has contributed to his expertise in data-driven approaches within the digital media landscape.
Education and Expertise
Thomas Lysensoone holds a Bachelor of Science degree from Lycée Henri Wallon, where he studied from 2011 to 2014. He furthered his education by obtaining a Master of Science degree in Applied Mathematics from Ecole centrale de Nantes from 2014 to 2016. Additionally, he completed another Master of Science degree in Machine Learning and Signal Processing at DTU - Technical University of Denmark from 2016 to 2018. His educational background supports his specialization in data-driven sports betting.
Background
Thomas Lysensoone is based in Lille, Hauts-de-France, France. He began his professional career at Hertz, where he worked as a Continuous Improvement Assistant Manager for one month in 2015 in Montigny-le-Bretonneux. His early experience in this role laid the groundwork for his transition into data science, where he has since focused on leveraging data for strategic insights.
Professional Experience
With over three years of experience in the field of data science, Thomas Lysensoone has developed a strong foundation in data analysis and interpretation. His work at Jellysmack and previous internship experiences have equipped him with the skills necessary to tackle complex data challenges, particularly in the realm of sports betting. His career trajectory reflects a commitment to advancing his knowledge and applying data science in practical settings.