Matthew MacFarlane

Delivers NLP and data science capabilities for a Ukrainian publishing firm, applying ML to literary content analysis, audience segmentation, and translation quality assurance. Builds and maintains multi-agent AI translation pipelines for Ukrainian-to-English literary and civic texts.

Led the first AI-assisted translation of a Ukrainian leadership book into English using LangChain, now available on Amazon and in bookstores. Authored the afterword and managed a cross-functional team of translators, editors, and ML engineers.

Prototyped and benchmarked an autonomous AI agent workflow for generating comparative intelligence and threat research reports. Integrated multi-agent validation loops and RAG pipeline mechanisms to reduce hallucination rates and verify analytical lineage.

Supported development of a digital platform coordinating humanitarian aid for internally displaced persons in Ukraine.

Designed a dynamic tagging system for constituent correspondence using data classification and automation techniques. Managed the L2 voter database, organizing 499+ targeted mailers through data-driven segmentation strategies.

Migrated campaign website to NationBuilder and executed a successful ballot access petition campaign using data-driven voter targeting.

Managed staff, volunteers, and voter database systems (i360, TrailBlazer, NationBuilder) for data-driven outreach.

Pursuing an MS in Applied Data Science with an Applied Machine Learning track, advised by Prof. Bernhard Klingenberg.

Completed Full Stack Web Development and Data Science programs covering Python, Flask, JavaScript, and NLP.

Studied Art, Philosophy, and Literature; received an Honorable Discharge in July 2015.

Earned a Bachelor of Science in Political Science.