Sean Carrell is a data scientist with eight years of experience blending rigorous academic training (PhD in Mathematics) with industry leadership at Shopify and Meta. He has led cross-disciplinary teams to deliver executive and external insights, translating complex quantitative analysis into strategic decisions for senior leaders and merchants. His background in teaching and research gives him a knack for clear communication of technical concepts to both specialist and general audiences. Hands-on ML engineering work—such as contributing sentiment-analysis and deployment notebooks for AWS SageMaker—shows he moves models from experimentation to production. Based in Kitchener, Ontario, he combines deep theoretical foundations with practical deployment experience and a track record of organizing educational and seminar programs.
8 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Mathematics, Doctor of Philosophy (Ph.D.) Mathematics at University of Waterloo
Code and associated files for the deploying ML models within AWS SageMaker
Role in this project:
ML Engineer
Contributions:27 commits, 4 pushes in 4 months
Contributions summary:Sean's primary contributions focus on developing and integrating machine learning models within the AWS SageMaker environment. The commits demonstrate the addition of sentiment analysis notebooks using XGBoost and PyTorch, indicating model development and implementation. Furthermore, the code changes suggest involvement in deploying ML models, exemplified by the custom model API notebook, and include the use of batch transform for model testing, and web app development.
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