I am a seasoned Machine Learning with over a decade of experience in Statistical Modeling, Machine Learning, and AI, seamlessly transitioning from a strong foundation in data science. Throughout my career, I have delivered impactful solutions across diverse industries such as Retail, Public Sector, Healthcare, and Financial Services. With a deep expertise in natural language processing (NLP) and generative AI, I have spearheaded the development of cutting-edge applications leveraging large language models (LLMs) and retrieval-augmented generation (RAG) techniques. My recent work includes building an innovative RAG-based LLM application using open source LLMs to extract granular product and promotional information from vast amounts of unstructured data, enabling crucial pricing KPIs. In my current role as a Sr Data Scientist/Machine Learning Engineer at GFK, London, I excel in building and maintaining pricing insights using MLOps principles, and I have demonstrated expertise in production-level Python coding. I actively contribute to code reviews and provide constructive feedback to ensure high-quality code. My technical skills include expertise in ML, GenAI, Python, R, Git, Docker, and MLOps, with a proven track record of leading data science transformation projects. I bring a unique blend of technical prowess and product development capabilities, having successfully taken projects from Proof of Concept to Production. Skills set: ▪ Languages & Frameworks: Python, SQL, TesnorFlow, PyTorch, LangChain, transformers, spaCy, scikit-learn ▪ Machine Learning, LLMs, Deep Learning, Statistics, Forecasting ▪ MLOps: GitHub, GitLab, Docker, FastAPI, Vector DB, MLflow, Comet ▪ Cloud: GCP, Azure, AWS, Beam ▪ Project Management/ Documentation: Jira, Confluence, Miro