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Bala Venkateswarlu K
Mid-level Data Scientist specializing in Generative AI, NLP, and MLOps
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About
Built and deployed an LLM-powered claims-document summarization system (insurance domain) that cut agent review time from 4–5 minutes to under 2 minutes and saved 1,200+ hours per quarter. Hands-on across orchestration and production infrastructure (Airflow retraining DAGs, Kubernetes, SageMaker endpoints, FastAPI) and recent RAG workflows using n8n + Pinecone, with a strong focus on reliability, cost, and explainability for non-technical stakeholders.
Experience
Education
Key Strengths
- Deployed LLM claims summarization system reducing review time from 4–5 minutes to under 2 minutes (45% faster)
- Delivered measurable operational savings (1,200+ human hours saved quarterly)
- Production-minded approach to privacy/security (encryption, data privacy protocols) for sensitive claims data
- Built and operated orchestration at scale (Airflow daily ML retraining DAGs with 50+ tasks)
- End-to-end deployment experience (Kubernetes + SageMaker endpoints + FastAPI services)
- Practical RAG implementation and optimization (chunking strategy, batched upserts, namespaces)
- Reliability engineering for AI workflows (contracts, modular design, observability, unit/integration/chaos testing)
- Clear performance metrics orientation (task success rate, 99% uptime target, <$0.01/query cost target)
- Effective non-technical stakeholder collaboration via demos, dashboards, confidence scores, and explainability
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