Bharath Chengalva
Data Scientist @HCA Healthcare
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WORK HISTORY
Data Scientist @HCA Healthcare
Carrollton, TX, US
Developed and deployed advanced machine learning models for healthcare analytics, implementing custom CNN-LSTM hybrid architectures for time-series medical data analysis, optimizing patient risk assessment (AUC 0.91) and operational efficiency. • Designed and automated end-to-end data pipelines using Apache Airflow, Spark, and SQL, reducing data processing optimization by 30% across multiple healthcare systems. • Leveraged AWS (SageMaker, Lambda, Step Functions) and GCP (Vertex AI, Dataflow) to deploy scalable ML models and automate workflows, improving model retraining efficiency. • Designed containerized ML solutions with Docker and Kubernetes, implementing blue-green deployments with Helm charts and ArgoCD for zero-downtime updates of healthcare prediction systems. • Developed and deployed NLP solutions using BERT-based transformers for document classification, reducing manual workload by 40%, and extended NLP applications to sentiment analysis and chatbot automation. • Built CI/CD pipelines for real-time model retraining and deployment using Docker, Kubernetes, Jenkins, and MLflow, ensuring efficient model lifecycle management. • Implemented a comprehensive A/B testing framework using Python and FastAPI to evaluate model performance across different patient cohorts, leading to a 22% improvement in prediction accuracy. • Optimized model serving using TensorFlow Serving and FastAPI, improving low-latency inference and scalability for real-time healthcare predictions. • Designed RESTful APIs to integrate ML models with healthcare applications, ensuring high availability and low-latency predictions.
EDUCATION
Sreenidhi Institute of Science and Technology
Bachelor of Technology - BTech, Electrical, Electronics and Communications Engineering
University of North Texas
Master's degree, Computer Science
ABOUT BHARATH CHENGALVA
Results-driven Data Scientist with 4+ years of experience in building scalable machine learning models, optimizing data pipelines, and deploying AI-driven solutions. Adept at predictive analytics, customer segmentation, and fraud detection, driving business impact through data-driven strategies that enhance revenue growth and operational efficiency. Proficient in cloud computing (AWS, GCP,AZURE), MLOps, and data visualization tools (Power BI, Tableau). Skilled in big data technologies (Spark,Hadoop,Kafka) for real-time data processing. Experienced in deep learning techniques including transformers (BERT, GPT), LSTMs, and NLP applications. Strong background in end-to-end model development, deployment, and monitoring, ensuring scalable and production-ready AI solutions.
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