I’m a Full-Stack Data Scientist and AI Engineer who excels at bridging business objectives with cutting-edge data/AI solutions. My expertise spans the entire data science pipeline—everything from mapping out the right business problem to developing data engineering workflows (ETL, warehousing, and integrations) and performing in-depth data exploration (EDAs, feature engineering, optimization). I’m fluent in a broad range of techniques, including traditional ML (k-means, SVMs, regression models, dimensionality reduction) and deep learning methods (Transformers, CNNs, RNNs, autoencoders). On the generative AI side, I work with GANs, large language models, foundation models, and fine-tuning. Though I consider myself a generalist, my passion lies in NLP—I love building language-focused systems using advanced architectures like GPT and BERT, exploring Deep RL, and experimenting with agentic AI approaches. This breadth and depth equip me to solve complex challenges, whether in finance/fintech, healthcare, or any data-driven domain. As a strategic problem-solver and thought leader, I’m driven by intellectual curiosity, innovation, and a passion for collaboration and mentorship. Dynamic by nature, I thrive in environments that encourage experimenting with new ideas and pushing technical boundaries. Ultimately, I'm dedicated to creating transformative, high-impact, and innovative solutions that drive success.