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Andrew Clayman
Senior Data Scientist specializing in ML, NLP, and production AI systems
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About
Machine learning/NLP engineer with deep Azure stack experience (Data Factory, Databricks/Spark, Delta Lake, Azure OpenAI, Azure AI Search) who built end-to-end production systems for semantic clustering, entity resolution, and hybrid search. Demonstrated measurable gains from embedding fine-tuning (~15% retrieval precision, ~10–12% nDCG@10) and designed scalable, quality-checked pipelines with MLOps best practices.
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Key Strengths
- Built production-grade NLP pipeline linking unstructured reviews to sales/ops data
- Scalable entity resolution design using blocking + LSH/vector search + ML re-ranking
- Maintained ~95%+ precision in entity matching with manual review + automated quality checks
- Improved retrieval/search relevance via embedding fine-tuning with rigorous offline + online evaluation (A/B tests)
- Strong MLOps practices (MLflow, Docker, CI/CD, monitoring, idempotent pipelines, testing)
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