Joonil Ahn is a Principal Associate in Data Science with 8 years of experience building and productionizing ML solutions for finance and insurance, currently driving credit risk modeling and model pipelines at Capital One. He combines strong engineering rigor (Kubeflow, BigQuery, AWS/GCP) with deep learning expertise—having led OCR/text-recognition and image classification systems that slashed manual review by 90% and accelerated prototyping via a PyTorch library. His work spans XGBoost and neural approaches to improve AUROC and reduce training costs, while proactively owning model monitoring and cross-functional delivery. Trained as an industrial engineer (M.Eng., Univ. of Toronto) with an early mechanical engineering background, he blends analytical depth with practical systems-thinking to move experiments into scalable production.
8 years of coding experience
9 years of employment as a software developer
Bachelor of Science (B.S.), Naval Architecture and Marine Engineering, Bachelor of Science (B.S.), Naval Architecture and Marine Engineering at Seoul National University
Master of Engineering (M.Eng.), Industrial Engineering (Specialization in Analytics), 3.87 / 4.0, Master of Engineering (M.Eng.), Industrial Engineering (Specialization in Analytics), 3.87 / 4.0 at University of Toronto
Contributions:30 commits, 28 pushes, 1 branch in 4 years 4 months
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