Sathya Venkataramana Rao

Innovative data scientist with a robust background in machine learning, statistical analysis, and predictive modeling. Skilled in translating complex datasets into actionable insights that drive decision-making and business strategy improvements. Demonstrates strong problem-solving abilities and mastery of Python, R, SQL, and data visualization tools. Previous work has led to significant enhancements in operational efficiency and revenue growth through data-driven strategies.

• Breast Cancer Prediction, 08/2022 - 10/2022, University of Liverpool, A project focused on predicting breast cancer using ML models, Developed a machine learning pipeline using the Wisconsin Breast Cancer Dataset (569 cases), achieving 98% precision and 94% recall for malignant tumor detection., Project aligned with industry practices used in tools like NHS Predict v3 and research trials (e.g., MammaPrint MINDACT, n=6,693), reinforcing potential for clinical-scale application., Benchmarked multiple models (SVM, Random Forest, Logistic Regression), optimizing hyperparameters to reach >90% overall accuracy.
• Sewage Gas Detection System, 12/2018 - 04/2019, R.M.D Engineering College, An IoT-based project for detecting sewage gas, Built IoT sensor-based gas alert system with 95% detection accuracy, Helped reduce risk of hazardous exposure by simulating real-time monitoring, which in professional settings (e.g., NYC, India STPs) resulted in improved gas recovery and 50% fewer incident reports.
• Medical Storage Management System, 09/2017 - 09/2018, R.M.D Engineering College, A management system for medical inventory, Developed a real-time RFID-based storage system for hospitals using Total Sense cabinets and smart bins, automating item tracking and expiry monitoring to reduce expired inventory by 97%., Guided procurement strategy via analytics, yielding $2-3M annual savings and supporting transition to 100% vendor-managed consignment.