I specialize in leveraging cutting-edge Generative AI, Large Language Models and Machine Learning to craft responsible, scalable, and impactful AI solutions for millions of Microsoft users. My work sits at the intersection of deep tech and practical utility—translating the power of LLMs and AI into real-world innovations that enhance productivity and drive better user experiences. With a strong foundation in machine learning, statistics, economics and experimentation, I collaborate cross-functionally to build, test, and integrate AI-driven systems that solve diverse consumer and business challenges. From ideation to deployment, my focus remains on measurable impact and improved user experience. Core Strengths: - Applied GenAI and LLMs. - Expertise in traditional ML, A/B testing, and statistical modeling - Translating research into business impact through experimentation and agile development - Cross-functional collaboration with product, engineering, and design teams I hold a Master’s in Applied Data Science from the University of Chicago, where I developed a strong interdisciplinary base in neural networks, econometrics, behavioral economics, and decision theory—skills I regularly apply to real-world AI and data challenges at my work.