Ayoub Nasri
About Ayoub Nasri
Ayoub Nasri is a Data Science Intern currently working at Intact Insurance in Montréal, Canada. He has a background in Automated Production Engineering and has held various roles in software and research development, contributing to machine learning projects.
Work at Intact Financial Corporation
Ayoub Nasri currently serves as a Data Science Intern at Intact Insurance's data lab, a position he has held since 2021. In this role, he has been involved in various projects that leverage machine learning and statistical methods. Notably, he participated in the implementation of an automatic prediction algorithm, contributing to the organization's data-driven initiatives.
Education and Expertise
Ayoub Nasri is pursuing a Master's degree in Automated Production Engineering with a focus on machine learning at École de technologie supérieure (ÉTS), which he began in 2020. He previously completed a Bachelor's degree in the same field at ÉTS from 2018 to 2021. Additionally, he holds a DUT in Ingénierie mécatronique, robotique et automatisation from Ecole Supérieure de Technologie de Oujda (ESTO), which he completed from 2010 to 2012.
Background in Software and Research
Before his current role, Ayoub Nasri gained experience as a Specialist in aircraft systems software at CAE Inc. for three months in 2020. He also worked as a Research and Development Intern at CRCHUM in 2021 for four months, where he collaborated with a team on projects that involved machine learning and statistical approaches.
Previous Work Experience
In 2018, Ayoub Nasri worked as a Maintenance Technician at Alumico Architectural Inc. for three months. This role provided him with practical experience in maintenance and technical support within an industrial setting. His diverse work history reflects a strong foundation in both technical and engineering disciplines.
Technical Skills in Programming
Ayoub Nasri possesses programming skills in RAPID language, which is specifically utilized for industrial robotics applications. This expertise complements his educational background and enhances his capabilities in the field of automated production engineering.