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Preeti Pandey
Senior AI/ML Engineer specializing in predictive analytics and NLP
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ML/AI engineer with hands-on experience building production healthcare AI systems across predictive modeling and GenAI. They built an end-to-end patient risk prediction platform and a RAG-based clinical summarization feature, combining strong NLP/LLM skills with AWS deployment, monitoring, drift detection, and reusable Python service design to deliver measurable clinical and operational impact.
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Key Strengths
- Owned end-to-end ML system lifecycle from experimentation to deployment and monitoring
- Applied NLP and multimodal healthcare data techniques to patient risk prediction
- Improved model accuracy by about 28% using XGBoost and feature engineering
- Reduced processing time by around 35% in a clinical workflow
- Strong MLOps practices including drift detection, retraining pipelines, versioning, and staging validation
- Shipped RAG-based clinical summarization features with quality and safety evaluation
- Reduced clinician manual review time and improved insight extraction by about 30%
- Balanced latency, cost, quality, and safety tradeoffs in production GenAI systems
- Improved retrieval quality in production through embedding improvements and reranking
- Built reusable Python services and libraries that increased team velocity and system reliability
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