Final-year IT undergraduate specializing in REST APIs, ETL pipelines, and advanced data analytics.
GUJJULA SINDHURA is a final-year IT undergraduate adept in Python, specializing in building REST APIs, ETL pipelines, and advanced data analytics solutions. She has engineered an AI-powered resume screening system and developed a URL threat classification model, demonstrating a strong ability to drive efficiency through data-driven insights.
Expertise in developing AI-powered solutions, including LLM + RAG workflows, deep neural networks, and advanced machine learning algorithms for tasks like resume screening and threat classification.
Proficient in building end-to-end ETL pipelines, designing and exposing REST APIs, and containerizing microservices for scalable data processing and application integration.
Skilled in transforming raw data into actionable insights through customer segmentation, campaign analytics, and creating executive dashboards using leading visualization tools.
Experienced in deploying and managing services on cloud platforms, utilizing CI/CD pipelines, and containerization for robust and repeatable build-and-deploy processes.
Built an end-to-end ETL pipeline integrating LLM + RAG workflows and custom matching algorithms for semantic resume-to-JD comparison, extracting structured insights from unstructured data. Designed and exposed a REST API for the matching engine and deployed the service via an automated CI/CD pipeline on Vercel.
Impact: Reduced manual screening effort by 70% with sub-10s latency.
Designed a deep neural network algorithm (PyTorch) processing 100K+ samples and engineered 15+ features for URL threat classification. Built and containerized a production FastAPI microservice with Docker.
Impact: Improved recall from 67% to 81% and achieved 88.2% ROC-AUC, delivering sub-200ms classifications.
Built ETL pipelines to clean and warehouse 50K+ records, applying K-Means and PCA algorithms. Delivered executive dashboards via Power BI and Tableau, and documented data governance schemas.
Impact: Improved campaign targeting precision by ~25% and reduced campaign planning time by ~35%.
Certified as an Oracle Cloud Infrastructure 2025 Generative AI Professional.
Commenced B.Tech in Information Technology at VIT Vellore.
Achieved 88.2% ROC-AUC and 81% recall in a Real-Time URL Threat Classification model.
Reduced manual resume screening effort by 70% with an AI-powered system.
Improved campaign targeting precision by ~25% and cut planning time by ~35% using Power BI and Tableau.