Ajay Jagu
Data Scientist Ml Ai Engineer @Cardinal Health
Signup · Get unlimited contacts
WORK HISTORY
Data Scientist Ml Ai Engineer @Cardinal Health
OH, US
Developed a real-time healthcare analytics platform for processing structured and unstructured data, integrating machine learning models such as Random Forest and XGBoost to predict disease progression with over 92% accuracy. Leveraged large language models (LLMs) like GPT-4 and BERT via Hugging Face for medical text summarization and clinical decision support, enhancing patient query handling. Implemented time-series forecasting techniques to optimize hospital resource allocation. Built and deployed RESTful APIs using FastAPI, integrating with electronic health records (EHRs). Applied MLOps practices with Kubeflow and AWS SageMaker Pipelines for automated model retraining and CI/CD pipelines. Deployed on AWS, ensuring HIPAA compliance, utilizing Lambda and EC2 for scalability, and leveraging Docker and Kubernetes for containerization. Automated medical documentation, reducing clinician workload and increasing operational efficiency.
EDUCATION
KL University
Bachelor's degree
University of New Haven
Master's degree
ABOUT AJAY JAGU
At Cardinal Health, we are harnessing the power of LSTM and linear regression to predict disease progression with over 95% accuracy, a testment to the advanced time-series models my education and experience have empowered me to develop. My role interweaves my Master\'s in Data Science, focusing on patient outcomes through meticulous NLP and LLM application for critical care decision-making. • Experience in building ML, Gen AI End-to-End Applications using Python from Data Ingestion to Deployment. • Good Knowledge on understanding data and gathering data based on client business requirements. • Having good experience in Langchain Framework building RAG systems on the top of LLM\'s to enhance the output of the LLM. • Hands on experience on LLM\'s in building Gen AI Applications and building RESTFUL API\'s using FASTAPI. • Making Automation of the workflow of the application by building CI/CD pipelines. Good knowledge on • Cloud Platform like AWS services like EC2, Sage Maker, AWS Lambda.etc. Strong in Machine Learning, Deep Learning, NLP models and SQL. Familiar in building Front end applications using Streamlit, Flask and aslo in using Pytorch, Tensorflow, Scikit-learn.
This profile is compiled from publicly available professional sources. Unifers is not affiliated with or endorsed by LinkedIn. Request removal of this profile.