Professional Overview
I am a Data Scientist with hands-on experience in building and deploying end-to-end Machine Learning and Generative AI solutions. I have worked extensively with Python, SQL, and modern ML frameworks to solve real-world business problems, including predictive modeling, NLP pipelines, and Retrieval-Augmented Generation (RAG) systems. My experience includes working with large datasets, designing feature engineering pipelines, fine-tuning models, and integrating LLM-based solutions into production using tools like LangChain, Docker, and AWS. I focus on building scalable, practical, and impact-driven AI solutions that align with business goals and deliver measurable value.
Areas of Expertise
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
Data Science & Analytics
Extract business insights from raw data using statistical modelling, predictive analytics, A/B testing, and interactive dashboards.
NLP & Prompt Engineering
Build natural language processing systems, fine-tune large language models, and craft reliable production prompts for AI-powered products.
MLOps & AI Infrastructure
Architect scalable ML infrastructure — CI/CD for ML, model versioning, experiment tracking, monitoring, and cloud deployment on AWS, GCP, or Azure.
