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@pavandheeraj
Aspiring Data Scientist excited to work on ML, AI, and CV in fast-moving teams.
Versatile AI professional with hands-on experience in building and deploying machine learning and deep learning solutions using Python, Scikit-learn, TensorFlow, and PyTorch. Skilled in end-to-end data pipelines, model optimization, forecasting, and evaluation. Strong background in classical ML, computer vision, and NLP tasks. Also experienced with GenAI workflows such as retrieval-augmented generation (RAG), prompt engineering, and LLM applications using LangChain enabling adaptable solutions across modern AI systems.
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Work history, roles, and key accomplishments
Built a real-time ASR system using NeMo and LLM agents (LangChain, CrewAI). Developed CV models using MONAI (SwinUNETR, SegResNet) and Florence-2 for spine MRI analysis. Deployed AI workflows on Azure ML, achieving top 20% performance in internal benchmarks.
Improved model deployment speed by 40% through cloud-based CNN/VGG19 weather app built with AutoAI. Built ML models (K-Means, Decision Trees, Naïve Bayes) with GridSearchCV. Deployed vision and NLP models via Flask and Azure Cognitive Services. Gained hands-on experience in preprocessing, model building, and data visualization.
Degrees, certifications, and relevant coursework
M.Tech Integrated, CSE Specialization in Data Science
Grade: 8.67
Activities and societies: Student Member of the Health Club, participating in community events and organizing marathons to promote fitness and well-being. Contributed to initiatives on preventing foodborne illnesses, advocating for hygiene and public safety.
Pursued an integrated Master of Technology in Computer Science with a specialization in Data Science. Achieved a GPA of 8.67, demonstrating strong academic performance in the field.
Software and tools used professionally
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