Stephen Stark

Senior Data Scientist @YETI

Chicago, IL, US
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WORK HISTORY

Oct 2022 — Present

Senior Data Scientist @YETI

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Chicago, IL, US

Lead applied AI initiatives spanning generative AI, predictive modeling, and NLP-driven systems across e-commerce, operations, and risk domainsDesigned and deployed an NLP clustering engine analyzing 500K+ customer-generated text records, uncovering new segmentation insights and informing digital strategyBuilt LLM-powered document parsing and workflow automation systems to reduce manual review and improve operational efficiencyDeveloped predictive models supporting revenue optimization and customer behavior insights across digital channelsAnalyzed large-scale conversational query data to enhance AI-driven product discovery and customer engagement toolsOwn initiatives end-to-end, from problem framing and data engineering through production deployment and stakeholder adoption

EDUCATION

N/A

Heritage Hall High School

Diploma, High School

N/A

SMU: Study Abroad in Paris

Study Abroad Program, History and Religion

N/A

SMU Cox School of Business

Bachelor's Degree, Finance

2019 — 2021

University of Chicago

Master of Science, Analytics, Data Science, Applied Statistics

N/A

DIS: Danish Institue for Study Abroad

Study Abroad, International Finance

ABOUT STEPHEN STARK

Senior Applied AI leader building enterprise-scale machine learning and LLM systems at YETI.I design and deploy customer-facing AI products and internal generative AI platforms — from NLP clustering engines analyzing 500K+ transactions to LLM-powered workflow automation supporting enterprise operations.My work spans the full lifecycle of applied AI systems: problem framing, modeling, experimentation, productionization, and cross-functional stakeholder alignment. I focus on translating ambiguous business challenges into scalable, data-driven solutions that drive measurable impact.Technically, I work primarily in Python, SQL, and PySpark, building machine learning and LLM-powered systems using modern embedding models, clustering and anomaly detection techniques, API integrations, and scalable data infrastructure.

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