Tejaswini Gaderaboina

Data Engineer specializing in scalable cloud-based platforms and advanced ETL/ELT pipelines. Developed and optimized data lake solutions that improved query performance by 45%, while automating workflows using Apache Airflow, resulting in a 55% reduction in data issues.

• Machine Learning Driven Object Detection Application, Designed and developed a real-time object detection application using deep learning and computer vision techniques. Improved model accuracy from 74% to 83.3% through hyperparameter tuning and optimization while reducing inference latency by 25%. Built scalable REST APIs for model deployment and reusable software components.
• Physiological Sensor Data Modeling, Developed machine learning models for predictive analytics using physiological sensor data. Performed data preprocessing, feature engineering, and model validation, achieving approximately 88% prediction accuracy. Tracked experiments with MLflow to ensure reproducibility and model performance.
• Social Network Spam Detection System, Built supervised machine learning models to detect fake social network accounts using user behavior and metadata. Improved classification performance by 20% through feature engineering and evaluated models using industry-standard metrics.