Firas Rhimi
About Firas Rhimi
Firas Rhimi is a Data Scientist with experience in both France and Tunisia. He holds a Master of Science in Data Sciences and has worked at notable companies such as Teads, Saint-Gobain, and Ermes.
Current Role at Teads
Firas Rhimi has been working as a Data Scientist at Teads since April 2021. In this role, he applies his expertise in data science to contribute to the company's projects and initiatives. His experience encompasses various aspects of data analysis, machine learning, and statistical modeling, which are essential for driving insights and decision-making within the organization.
Previous Experience in Data Science Internships
Prior to his current position, Firas Rhimi gained valuable experience through several internships in data science. He worked as a Data Science Intern at Saint-Gobain for two months in 2019 in the Région de Paris, France. Additionally, he completed a five-month internship at Ermes in Ville de Paris, Île-de-France, France, in 2020. These internships provided him with practical skills and exposure to real-world data science applications.
Educational Background in Data Sciences
Firas Rhimi has a solid educational foundation in data sciences. He studied at École Polytechnique, where he achieved a Master of Science in Mathematics and Applications: Data Sciences from 2019 to 2020. Prior to that, he attended Ecole Nationale Supérieure des Mines de Nancy, earning a Diplôme d'ingénieur in Mathematical Engineering from 2017 to 2020. He also studied at IPEST: Preparatory Institute for Engineering Studies in La Marsa, Tunisia, focusing on Mathematics-Physics from 2015 to 2017.
Internship Experience at SOPAL
Firas Rhimi completed a one-month Operator Internship at SOPAL in 2018, located in Sfax Governorate, Tunisia. This early experience provided him with insights into operational processes and helped him develop foundational skills that would support his future endeavors in data science.
Expertise in Data Science and Machine Learning
Firas Rhimi has a strong interest in data science, machine learning, and statistics. His educational background and professional experiences have equipped him with the necessary skills to excel in these fields. He continues to engage with emerging trends and technologies to enhance his expertise and contribute effectively to his work.