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Bernard Griffin
Senior Data Scientist / ML Engineer specializing in cloud ML pipelines and GenAI
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ML/NLP practitioner with experience building a transformer-failure prediction system that combines sensor signals with unstructured maintenance comments using LLM-based extraction and similarity validation. Strong emphasis on production readiness—data leakage controls, SQL-driven data quality tiers, and rigorous bias/fairness validation (including contract/spec evaluation across diverse company profiles).
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Key Strengths
- Built predictive model for transformer failure using sensor data plus maintenance comments
- Applied LLM-based extraction and sentence chunking to structure unstructured maintenance text
- Used similarity metrics (cosine) to validate text/embedding proximity
- Strong focus on preventing data leakage (placeholders during sensor downtime)
- Baseline modeling with feature importance to refine feature set
- Designed data quality tiers (gold/silver/bronze) via SQL for production modeling
- Emphasis on production reliability: guardrails, hallucination checks, bias/fairness validation, stress testing
- Experience validating model fairness across different company sizes and demographics in contract/spec evaluation
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