"Never let success go to your head and never let failure go to your heart" -Ziad K.Abdelnour
I’m a data scientist passionate about building scalable machine learning solutions that drive measurable impact. At Kohl’s, I led the design and deployment of a Hybrid Matrix Factorization recommender system serving over 20 million customers, resulting in a $13.8M revenue lift. I also developed a long range forecasting model to predict inventory arrivals at U.S. ports, improving 6-month forecast accuracy by 67%. My work spans personalization, forecasting, and MLOps.
Outside of industry, I’m an adjunct professor at the University of Denver, where I teach graduate level courses in machine learning and database systems. I’m also a published contributor on Towards Data Science and KDnuggets, and an award-winning Streamlit app developer.
With experience across retail, supply chain, sports analytics (formerly with Vancouver Whitecaps FC), and academia, I’m driven by the intersection of data, engineering, and decision-making. I’m always eager to learn, collaborate, and mentor the next generation of data professionals.
If you would like to learn more about me, feel free to have a look at my resume.
