Matthew Boyd is a software engineer based in Oakland with a decade-plus track record specializing in back-end data ingestion, normalization, and transformation for analytics and ML pipelines. He has built scalable ETL systems that expanded legal-data coverage by millions of cases and prototyped predictive monitoring to detect silent ingestion failures. Most proficient in Python, he moves proof-of-concept analyses into production—turning Jupyter notebooks into deployed Django services with automated AWS pipelines for startups on tight timelines. His experience spans enterprise and editorial systems, from modernizing version control and automating publishing workflows to extracting structured web data at scale. Colleagues rely on him for pragmatic performance optimizations and workflow improvements that boost team productivity. He combines a journalism background with engineering rigor, which sharpens his focus on clean, auditable data for downstream ML and product use.
9 years of coding experience
15 years of employment as a software developer
Bachelor's degree Journalism, Bachelor's degree Journalism at University of Maryland
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