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@anerigirishbhaipatel
Data scientist specializing in NLP, LLM integration, and scalable ML-driven solutions.
I am a data scientist focused on NLP and large language model integration, with hands-on experience building scalable pipelines, deploying models on cloud platforms, and optimizing inference workflows. I have delivered production-ready applications—ranging from serverless RAG chatbots to document-summarization web apps—improving efficiency and retrieval accuracy in legal and educational contexts.
My background combines strong applied ML engineering skills (PyTorch, TensorFlow, CUDA optimization), cloud and DevOps practices (GCP, AWS, Docker), and data engineering (ETL, SQL, Airflow). I emphasize iterative, user-informed development: my projects have reduced manual review time by 23%, achieved 90% retrieval accuracy in production RAG systems, and supported analytics for 50,000 students.
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Work history, roles, and key accomplishments
The George Washington University
Jun 2024 - May 2025 (11 months)
Designed relational data models and implemented a Caspio-based ingestion system for metadata from 1,000+ litigation cases and 10,000 legal documents, and developed a GCP-deployed LLM summarization web app that reduced manual review time by 23%.
Infotrend Inc.
Jun 2024 - Aug 2024 (2 months)
Built and fine-tuned NLP and computer vision models using PyTorch and TensorFlow, optimized inference with CUDA and post-training quantization to improve inference speed by 30%, and containerized models with Docker for deployment.
Degrees, certifications, and relevant coursework
Master of Science, Data Science
2023 - 2025
Grade: 3.97/4.00
Master of Science in Data Science with coursework in data mining, algorithm design, and data visualization; graduated with a 3.97/4.00 GPA.
Bachelor of Science (Hons.), Artificial Intelligence and Machine Learning
2019 - 2023
Grade: 3.6/4.00
Bachelor of Science (Hons.) in Artificial Intelligence and Machine Learning with a focus on cloud computing; completed with a 3.6/4.0 GPA.
Software and tools used professionally
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