• Seasoned Data Scientist & ML Engineer with 4+ years of extensive experience in developing, deploying, and optimizing ML and artificial intelligence models, particularly in natural language processing and large language models (LLM)• Proficient in advanced statistical analysis, AI algorithms, and predictive modeling with a strong background in Python, R, and SQL for data manipulation, feature engineering, and model development.• Expertise in large language models (LLMs) and AI technologies, including fine-tuning and deploying models like GPT-4, BERT, and other transformer architectures to solve complex natural language understanding tasks• Well-versed with major LLM including GPT, Claude, Llama, and Gemini, enhancing NLP capabilities through advanced techniques such as Retrieval Augmented Generation (RAG) and Zero-Shot/Few-Shot learning• Experienced in A/B testing and experimental design, achieving significant improvements in user engagement and conversion rates by applying data-driven insights to product features• Proficient in data wrangling using Python libraries including NumPy, Pandas, and Scikit-Learn, as well as SQL databases such as MySQL and PostgreSQL, to clean, transform, and prepare data for analysis• Proficient in utilizing Python 3. X, TensorFlow, PyTorch, Transformers, Scikit Learn, LangChain, Boto3, and Haystack to address a wide range of ML and NLP challenges, delivering robust and scalable solutions• Strong proficiency in data visualization and storytelling, using tools like Tableau, Power BI, and Matplotlib to create compelling, actionable insights for stakeholders• Expertise in deploying ML models to production in AWS Bedrock and Azure Machine Learning, leveraging CI/CD pipelines, Docker for containerization, and Kubernetes for orchestration to ensure high availability and scalability• Adept in deploying and managing machine learning and AI models on cloud platforms such as AWS, and Azure, ensuring scalability and performance optimization• Expert in developing MLOps pipelines using AWS SageMaker, ensuring streamlined model deployment, monitoring, and management for robust and scalable machine learning solutions• Solid experience with version control and collaborative development workflows, utilizing Git, GitHub, and Agile methodologies to streamline project delivery and improve code quality