Vijay Vanapalli
Data Scientist (Ai Ml Engineer) @Tata Consultancy Services
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WORK HISTORY
Data Scientist (Ai Ml Engineer) @Tata Consultancy Services
AI-Powered Banking Conversational Assistant | Jun 2024 – Present Architected end-to-end RAG pipeline using LangChain, Llama-2-7B, and ChromaDB to process banking documents, achieving 92% query accuracy and <2s response time Implemented real-time ML inference system with AWS Lambda, Kinesis, and custom NLP models for fraud detection and sentiment analysis, reducing customer service costs by 40% while maintaining 99.9% uptime Designed vector embedding optimization using sentence-transformers and semantic chunking algorithms, improving knowledge retrieval precision by 35% Built production MLOps pipeline with automated model retraining, A/B testing framework, and performance monitoring using CloudWatch metrics, processing daily conversations with continuous RLHF optimizationReal-Time Banking Fraud Detection System | Jun 2023 – May 2024 Developed and deployed ensemble ML models for fraud detection with 95% precision and <2% false positives. Automated model tracking and A/B testing using MLflow and GitHub CI/CD with zero downtime. Created Grafana dashboards for daily transactions monitoring.Customer Churn Prediction Platform | Jul 2022 – May 2023 Strategically reduced customer attrition by 23% through innovative classification models and feature engineering. Deployed models on EC2 with CI/CD automation and 99.9% system uptime. Enabled early retention action via customer risk scoring API
EDUCATION
Jawaharlal Nehru Technological University Kakinada (JNTUK)
Engineer's degree
ABOUT VIJAY VANAPALLI
Tata Consultancy Services empowered the development of advanced machine learning solutions and automated AWS pipelines, significantly reducing manual review efforts. Through collaborative efforts, the team deployed real-time fraud detection models with 95% precision and seamless CI/CD pipelines, ensuring uninterrupted model upgrades. With a strong foundation in engineering from JNTUK, expertise in MLOps, and certifications in Azure, contributions include building RFM-based clustering models to optimize retail campaigns and creating visually compelling dashboards using Power BI. Motivated by a passion for leveraging data-driven insights, the goal remains to implement scalable AI solutions that drive transformative business outcomes.
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