Juvail Ms

Generative AI and Data Science professional with experience at S&P Global building AI applications using Python, AWS Bedrock, and SageMaker. Skilled in developing LLM-based solutions, prompt engineering, and machine learning for real-world use cases. Experienced in building interactive applications with Streamlit and optimizing model performance, including GPU-based workloads. Strong foundation in statistical modeling and NLP.

Generative AI Apprentice at S&P Global (2024-12 – Present)

Commodity Insights (Product Operations)

• Engineered Generative AI solutions with Python and AWS Bedrock for multi agent document analysis and intelligent extraction
• Designed prompt engineering workflows using using GPT-based LLMs to improve accuracy and performance
• Developed AI agents integrating enterprise data with LLM reasoning for automated decision support
• Built interactive Streamlit applications to showcase Generative AI use cases to stakeholders
• Implemented document segmentation and vector embeddings using Hugging Face Transformers for semantic search
• Applied BERT models for text processing, classification, and embedding generation
• Deployed AI/NLP models on GPU-enabled virtual machines for scalable performance
• Utilized AWS SageMaker and S3 for model deployment, data processing, and AI pipelines
• Managed code versioning and collaboration via Git and GitHub
• Contributed to AI innovation initiatives and technical discussions enhancing team AI capabilities

Master of Science in Data Analytics – Bharathiar University (2022 – 2024)

Bachelor of Science in Statistics – Sri C Achuthamenon Government College (2018 – 2021)