Senior Data ScientistChicago, IL
Designing agentic AI, recommendation, communication, and semantic-knowledge capabilities across a large property-services ecosystem, with an emphasis on evaluation and technical leadership.
Experience / 2017—Now
From adaptive research to production AI.
A career centered on decision systems: research the learning problem, build the data and ML foundation, then make the result useful inside a real workflow.
- Agentic AI
- Recommendations
- ML Platforms
- Technical Leadership
Career timelineSystems that have
Systems that have
to work.
Data Scientist IISMS Assist
Delivered location-scale scoring releases, machine learning pipelines, and cloud data workflows for operational decision systems.
Data Services InternAssurant
Supported data-centric applications and Data as a Service capabilities using Python, SQL, and applied machine learning patterns.
Ph.D. ResearcherUniversity of Illinois Chicago
Researched online meta-learning, deep-learning optimization, and continuous model adaptation for smart-grid applications.
CapabilitiesThree layers of
Three layers of
applied AI work.
Agentic AI systems
Routing, grounding, semantic context, behavioral evaluation, and human review.
Recommendation systems
Candidate fit, operating constraints, availability, ranking, and outcome feedback.
ML and data platforms
Production pipelines, cloud workflows, model releases, monitoring, and adaptation.
Research asks what can learn. Production asks what can keep working.
Selected workSee the systems
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