Jo Frabetti is an MLOps Engineer with a decade of experience building production-ready machine learning systems and data visualizations for enterprises across healthcare, telecom, and finance. He combines hands-on model development in Python and R with infrastructure-as-code and cloud-native deployment using AWS (CDK, CloudFormation, Lambda, Step Functions), Azure, Docker, Kubernetes and Terraform. Jo has a strong background in turning research and notebooks into maintainable services—deploying Shiny and Streamlit pilots, defining C4 architectures, and implementing CI/CD pipelines for serverless and multi-container platforms. His earlier analytics work at AT&T and the San Diego Supercomputer Center showcases deep time-series and anomaly detection expertise, plus a patent-linked contribution on predictive DBMS tuning. Based in New York, he excels at bridging data science, frontend developers and ops teams to deliver auditable, production ML applications. Colleagues rely on him not only for technical delivery but for translating complex analyses into clear, actionable visualizations and services.
10 years of coding experience
13 years of employment as a software developer
BS Marketing / Finance, BS Marketing / Finance at Northeastern University
Master of Business Administration - MBA Finance and Statistics, Master of Business Administration - MBA Finance and Statistics at NYU Stern School of Business
Certificates Data Mining and Programming, Certificates Data Mining and Programming at UC San Diego Extended Studies
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Jo Frabetti - MLOps Engineer at New York Life Insurance Company