Dalia Abdou
About Dalia Abdou
Dalia Abdou is a Machine Learning Developer Intern at Kinaxis, where she has worked since 2021. She has a background in Computer Science and Statistics from McGill University and has held various roles in data science and software development.
Work at Kinaxis
Dalia Abdou has been employed at Kinaxis as a Machine Learning Developer Intern since 2021. In this role, she focuses on developing and implementing machine learning models to enhance supply chain management solutions. Her work contributes to the company's mission of providing real-time insights and improving decision-making processes for clients.
Previous Experience in Data Science
Before her current position, Dalia Abdou worked as a Data Scientist at CANN Forecast from 2019 to 2020. During her seven-month tenure, she was involved in analyzing data and developing predictive models to support forecasting efforts. This role provided her with valuable experience in data analytics and model development.
Internship Experience
In 2020, Dalia Abdou completed a seven-month internship as a Software Developer at UltraSense. This position allowed her to gain practical experience in software development, where she contributed to various projects and enhanced her programming skills. Her internship experience laid a foundation for her future roles in machine learning and data science.
Involvement with POWE McGill
Dalia Abdou volunteered with POWE McGill (Promoting Opportunities for Women in Engineering) from 2018 to 2019 for a duration of 11 months. As a Caravan volunteer, she participated in initiatives aimed at encouraging and supporting women pursuing careers in engineering. This involvement reflects her commitment to promoting diversity and inclusion in the engineering field.
Education in Computer Science and Statistics
Dalia Abdou studied at McGill University, where she earned a degree in Computer Science and Statistics from 2018 to 2022. Her education provided her with a strong foundation in programming, data analysis, and statistical methods, equipping her with the skills necessary for her roles in machine learning and data science.