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Hello, I’m Sreya Nunna, a graduate student specializing in AI, ML, and environmental data science. I’m currently pursuing a Master’s in Data Science and Machine Learning at Imperial College London, where I’m building predictive models and exploring graph-based data representations. I’m passionate about turning unstructured data into actionable insights through intelligent data pipelines, prompt engineering, and LLM applications. My work spans weather forecasting, sustainable site selection, and knowledge graphs, with hands-on experience in Python, PyTorch, and cloud-enabled deployments.…Hello, I’m Sreya Nunna, a graduate student specializing in AI, ML, and environmental data science. I’m currently pursuing a Master’s in Data Science and Machine Learning at Imperial College London, where I’m building predictive models and exploring graph-based data representations. I’m passionate about turning unstructured data into actionable insights through intelligent data pipelines, prompt engineering, and LLM applications. My work spans weather forecasting, sustainable site selection, and knowledge graphs, with hands-on experience in Python, PyTorch, and cloud-enabled deployments.

Sreya Nunna

AI Engineer, Data Scientist, Full Stack Developer, +2

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Hello, I’m Sreya Nunna, a graduate student specializing in AI, ML, and environmental data science. I’m currently pursuing a Master’s in Data Science and Machine Learning at Imperial College London, where I’m building predictive models and exploring graph-based data representations. I’m passionate about turning unstructured data into actionable insights through intelligent data pipelines, prompt engineering, and LLM applications. My work spans weather forecasting, sustainable site selection, and knowledge graphs, with hands-on experience in Python, PyTorch, and cloud-enabled deployments.…Hello, I’m Sreya Nunna, a graduate student specializing in AI, ML, and environmental data science. I’m currently pursuing a Master’s in Data Science and Machine Learning at Imperial College London, where I’m building predictive models and exploring graph-based data representations. I’m passionate about turning unstructured data into actionable insights through intelligent data pipelines, prompt engineering, and LLM applications. My work spans weather forecasting, sustainable site selection, and knowledge graphs, with hands-on experience in Python, PyTorch, and cloud-enabled deployments.

Available to hire

Hello, I’m Sreya Nunna, a graduate student specializing in AI, ML, and environmental data science. I’m currently pursuing a Master’s in Data Science and Machine Learning at Imperial College London, where I’m building predictive models and exploring graph-based data representations.

I’m passionate about turning unstructured data into actionable insights through intelligent data pipelines, prompt engineering, and LLM applications. My work spans weather forecasting, sustainable site selection, and knowledge graphs, with hands-on experience in Python, PyTorch, and cloud-enabled deployments.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Language

English

Fluent

Hindi

Advanced

Telugu

Advanced

Marathi (Marāṭhī)

Advanced

Work Experience

AI Engineer Intern at OpenWeather

May 1, 2025 - Present

Architected and deployed a 4-stage end-to-end semantic knowledge graph pipeline enabling natural language querying of multiple unstructured text data, integrating GPT-4-based query parsing, SentenceTransformer entity matching (all-MiniLM-L6-v2), bidirectional subgraph extraction, and FAISS-accelerated SPARQL generation, reducing query complexity for graph users. Implemented a comprehensive test suite using HotpotQA with 30+ curated question types, achieving end-to-end pipeline accuracy of 65% on multi-hop reasoning tasks while maintaining response times under 1.5 seconds.

DS & AI Product Testing and Feature Development at Smartail Pvt. Solutions

April 30, 2023 - October 25, 2025

Collaborated on AI-driven projects, including automated grading and compound detection, by analysing data and deploying ML pipelines to support efficient decision-making in education technology use cases. Built and evaluated models to support product features and testing for education technology.