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Edwin Tse
Junior Data Engineer specializing in BI, governed metrics, and workflow automation
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About
Built and shipped LLM/OCR/NLP-driven document-intelligence workflows in operational environments (EnvoyX and UPS), emphasizing production readiness via explicit state-machine orchestration, confidence gates, and human-in-the-loop review. Demonstrated strong business impact in customs brokerage/document ingestion: 50% fewer customs rejects, 30% higher throughput, SLA adherence improved from 71% to 96%, and platform reliability reaching 99.6% with 78% fewer bad-data incidents.
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Key Strengths
- Shipped production document-intelligence automation with confidence-gated routing and human review
- Designs multi-layer SLAs including data freshness, completion, recovery time, and data-quality integrity
- Builds predictable agent workflows using explicit state machines (not free-form autonomy)
- Closed-loop eval/monitoring tying model signals to business outcomes (reject rate, throughput, backlog aging, SLA adherence)
- Improved customs rejects by 50% and throughput by 30% via confidence gating and reviewer routing
- Raised SLA adherence from 71% to 96% by adding aging logic and escalation alerts
- Drove platform reliability to 99.6% and reduced bad-data incidents by 78%
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