Open to opportunities

VENKATA SAI CHANDRA VEERLAPALLY

@venkatasaichandravee

Message

I build scalable data pipelines and production RAG systems that improve retrieval, accuracy, and cost.

United States

Message

What I'm looking for

I'm looking to build production data, machine learning, NLP, and GenerativeAI systems where I can improve retrieval, automation, model performance, and decision-making at scale.

I'm building scalable data and ML pipelines at Georgia State University, where I designed Azure-based workflows that cut data processing time by 40% and accelerated model training and deployment.

I architected a production-oriented RAG system for natural-language search across unstructured documents, reducing retrieval time by 60%. I also built preprocessing and evaluation frameworks that improved retrieval accuracy by 30% and retrieval performance by 35%.

At Ameris Bank, I developed NLP models for marketing analytics and customer segmentation, improving targeted lead conversion by 15%. I also delivered Streamlit analytics applications and real-time inference pipelines with AWS Lambda and REST APIs.

Previously at DRDO, I integrated data from 31 heterogeneous sources and built validation frameworks achieving 99.5% data accuracy across more than 500K records annually. I bring hands-on experience across Python, SQL, cloud platforms, NLP, machine learning, and GenerativeAI.

Experience

Work history, roles, and key accomplishments

Current

Graduate Research Assistant

Current

Georgia State University

Jan 2025 - Present (1 year 8 months)

Designed scalable data and ML pipelines using Azure Machine Learning, Azure Data Factory, Python, and GitHub Actions, reducing data processing time by 40%. Architected a production-oriented RAG system for natural-language search, reducing retrieval time by 60% and improving retrieval accuracy by 30%.

Azure Machine Learning Azure Data Factory Python GitHub Actions RAG NLP LLM Ollama OpenAI API Recall@K Embeddings

Machine Learning Intern

Ameris Bank

May 2025 - Aug 2025 (3 months)

Developed NLP-based machine learning models for marketing analytics and customer segmentation, improving lead conversion rates by 15%. Built self-service analytics applications using Streamlit and Plotly, and designed real-time ML inference pipelines using AWS Lambda and REST APIs.

NLP Machine Learning Streamlit Plotly AWS Lambda REST APIs Python data preprocessing Feature Engineering

Data Analyst

DRDO

Dec 2023 - Jun 2024 (6 months)

Engineered data integration pipelines with Python and Apache Airflow, combining 31 heterogeneous sources for unified analytics. Implemented data validation and cleansing frameworks across over 500K records annually, achieving 99.5% data accuracy.

Python Airflow Data Integration Data Validation NumPy SQL scikit learn