shasheesh ch

I am an analytics-focused MBA (Analytics & AI) with a BS–MS in Computational Materials Science, blending strong mathematical foundations with hands-on experience in machine learning, generative AI, and data engineering. I build production-ready systems — from LLM-based agents and fine-tuned generative models to CatBoost pricing models and REST APIs deployed on Google Cloud — that turn complex data into actionable business insights.

My work spans telematics NLP agents, inspection analysis and custom messaging, used-car price estimation, and computational research in materials science. I prioritize pragmatic MLOps, data quality, and human-centric design to reduce manual effort, improve decision-making, and create scalable, maintainable ML solutions.

As a Data Scientist and Generative AI Specialist, I work at the intersection of data analytics and cutting-edge AI. I handle the full data pipeline—from data collection, cleaning, and exploratory analysis, to building and deploying machine learning models for classification, prediction, and clustering tasks. I also specialize in generative AI, leveraging models like GPT, Stable Diffusion, and custom transformers for text, image, and code generation, as well as prompt engineering and fine-tuning.

My work bridges business needs and AI innovation, turning raw data into insights and generative models into real-world applications—like intelligent chatbots, content creators, and recommendation systems—while ensuring ethical and safe AI practices.

Tech Stack:

Languages: Python, SQL,Bash

Libraries/Frameworks: Pandas, NumPy, Scikit-learn, TensorFlow, Hugging Face, LangChain

Tools: Collab, VS Code, MLflow, Alteryx

Platforms:GCP, Vertex AI

Databases: PostgreSQL, BigQuery

Visualization: Matplotlib, Seaborn, tableau

GenAI Models: GPT, LLaMA, Gemini