AI/ML Engineer at UnitedHealth Group

Improved patient risk scoring accuracy 28% using AWS SageMaker models, reducing readmissions 15% and supporting healthcare decision-making nationwide. Reduced data latency 40% by automating ETL workflows with Python, Pandas, SQL, and AWS S3 across healthcare systems. Ensured HIPAA compliance by integrating fairness monitoring frameworks, strengthening Responsible AI adoption across enterprise-level ML healthcare applications. Boosted workflow efficiency by deploying scalable Flask and FastAPI inference APIs for real-time healthcare decision support. Delivered actionable insights by developing reporting dashboards integrating predictive model outputs, improving executive healthcare decision-making processes. Increased model scalability with automated retraining workflows, ensuring consistent production accuracy and performance in healthcare applications. Strengthened cross-functional collaboration between clinicians, engineers, and data scientists to integrate AI-driven solutions into p

AI/ML Engineer at Hexaware Technologies

Reduced credit risk prediction errors 22% by building regression and classification models, enhancing financial portfolio quality significantly. Decreased manual review workload 35% by implementing CNN and RNN architectures using TensorFlow and PyTorch for NLP. Achieved 99.5% uptime by deploying Docker-based MLOps pipelines with CI/CD workflows across enterprise AI applications. Accelerated decision-making by embedding machine learning outputs into Power BI dashboards, providing executives with actionable business insights. Increased scalability through automated retraining workflows, improving model lifecycle management and reducing deployment overhead for clients. Accelerated reporting speed by applying deep learning architectures for text and image analytics across client enterprises. Improved cross-functional delivery by collaborating with BI teams and engineers to align ML outputs with KPIs.

ML Engineer at Hexaware Technologies

Increased e-commerce engagement 15% by developing recommendation systems that improved personalization and optimized targeted marketing campaigns. Maintained enterprise model accuracy by validating clustering, decision tree, and classification techniques for robust deployment. Enabled informed decisions by creating Tableau and Power BI dashboards presenting machine learning-driven insights. Reduced experimentation cycles 30% by optimizing workflows using Jupyter Notebook and Google Colab environments effectively. Improved personalization by applying clustering algorithms to customer behavioral data, generating actionable insights. Enhanced marketing campaign performance by integrating predictive machine learning outputs into strategy development processes. Supported scalable workflows by assisting senior AI engineers in enterprise-level machine learning project development.

AI/ML Engineer at UnitedHealth Group

Improved patient risk scoring accuracy by 28% using AWS SageMaker models, reducing readmissions by 15%. Reduced data latency by 40% by automating ETL workflows with Python, Pandas, SQL, and AWS S3. Ensured HIPAA compliance by integrating fairness monitoring frameworks. Boosted real-time decision support by deploying scalable Flask and FastAPI inference APIs. Delivered dashboards integrating predictive outputs and automated retraining workflows to sustain production accuracy. Collaborated with clinicians, engineers, and data scientists to deploy AI-driven healthcare solutions.

AI/ML Engineer at Hexaware Technologies

Reduced credit risk prediction errors by 22% by building regression and classification models. Decreased manual review workload by 35% by implementing CNN and RNN architectures for NLP with TensorFlow and PyTorch. Achieved 99.5% uptime by deploying Docker-based MLOps pipelines with CI/CD workflows. Embedded ML outputs into Power BI dashboards to accelerate executive decision-making. Automated retraining workflows to improve model lifecycle management and reduce deployment overhead. Enhanced reporting speed with deep learning for text and image analytics. Collaborated with BI teams to align ML outputs with KPIs.