Akhila Patlolla

Machine Learning Engineer @Cigna Healthcare

IL, US

Architected end-to-end ML pipelines integrating Apache Spark, AWS SageMaker, and Airflow, enabling scalable ingestion, preprocessing, model training, deployment, and monitoring across petabyte-scale healthcare datasets. •Implemented CNN-based medical imaging models with multi-GPU training (TensorFlow + CUDA), achieving 92% precision on anomaly detection while reducing training time by 35% through distributed learning. •Developed a fraud detection system combining XGBoost, anomaly detection, and deep learning ensembles, improving claim fraud detection accuracy by 15% and reducing false positives by 22%. •Automated real-time risk scoring APIs with FastAPI + AWS Lambda, cutting response latency by 40% and scaling seamlessly for millions of daily transactions. •Deployed explainable AI modules (LIME, SHAP) to enhance transparency in healthcare models, increasing stakeholder trust and regulatory compliance. •Conducted large-scale sentiment analysis on patient data using hybrid NLP (BERT + rule-based models), providing actionable insights that boosted customer satisfaction scores by 10%. •Designed KPI-driven monitoring dashboards in Tableau and Matplotlib, enabling executives to track model drift, data quality, and ROI in real time.

Chaitanya Bharathi Institute Of Technology

Bachelor of Engineering - BE

Chicago State University

Master's degree, Computer Science