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Alexander Smith
Junior Software Engineer and Data Scientist specializing in AI/ML systems
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About
Built production-grade automation and ML/data pipelines at Dun & Bradstreet and ThreadNotion, spanning large-scale document classification, country risk report automation, and resilient Playwright testing for dynamic AI chat workflows. Particularly strong in turning brittle or ambiguous systems into reliable, observable, end-to-end automated platforms.
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Key Strengths
- Built end-to-end large-scale Python data pipeline over ~17 million webpages
- Strong reliability engineering for ML/data systems
- Deep testing discipline across unit, integration, shadow, and validation checks
- Robust observability and drift monitoring for production pipelines
- Hardening flaky Playwright automation in dynamic AI-driven chat UIs
- Uses deterministic waits and semantic selectors to stabilize brittle UI automation
- Designs idempotent, recoverable stateful workflows
- Systematically diagnoses automation failures with logs, screenshots, DOM snapshots, and network traces
- Turns ambiguous manual analyst processes into structured automated workflows
- Balances automation quality with graceful degradation, fallback logic, and auditability
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