Aswith Reddy Sama
Data Scientist @Chicago Education Advocacy Cooperative
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WORK HISTORY
Data Scientist @Chicago Education Advocacy Cooperative
Chicago, IL, US
Designing interpretable regression and tree-based models to quantify revenue impact of pre- and post-show programming. • Planning integration POS transaction data, event schedules, and opt-in audience signals into predictive simulations. • Architecting FastAPI services and interactive dashboards to translate analytics into operational decisions.
EDUCATION
Illinois Institute of Technology
Master's degree, Artificial Intelligence
JB Institute Of Engineering and Technology (JBIET)
Bachelor's degree, Information Technology
ABOUT ASWITH REDDY SAMA
Hi there! I am Aswith Sama, I recently completed my Master’s in Artificial Intelligence at the Illinois Institute of Technology, where I built a strong foundation in machine learning, deep learning, and LLMs. I am especially interested in LLMs and enjoy turning complex AI concepts into working systems through clean, efficient programming. My goal is to grow into a highly skilled AI engineer who not only understands the theory but can also build reliable, real-world AI solutions.Currently, I am working as a Data Scientist at the ChiEAC, where I am developing end-to-end ML systems and working extensively on Retrieval-Augmented Generation (RAG) pipelines. My work involves designing data pipelines, structuring and chunking documents, building embedding-based retrieval systems, fine-tuning models, and deploying production-ready APIs. Through this, I am gaining hands-on experience in handling unstructured data, improving model performance, optimizing retrieval strategies, and ensuring scalable deployment, skills that are directly aligned with modern AI systems powered by LLMs.Alongside this, I continuously strengthen my understanding of data engineering and system design because building strong RAG and LLM applications requires more than just model knowledge. It requires clean data processing, thoughtful architecture, efficient storage and retrieval mechanisms, and robust deployment practices. My focus is on mastering the full pipeline, from raw data to intelligent, production-level AI systems.
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