As a principal ML engineer at Redpoll, I lead the development and deployment of cutting-edge AI/ML solutions that are explainable, trustable, and scalable. With over a decade of experience in data science and machine learning, I specialize in Bayesian methodologies that enable probabilistic inference, uncertainty quantification, and model interpretability.I have applied my expertise in various domains, such as agriculture, law, healthcare, and finance, delivering impactful and mathematically sound models that solve complex and real-world problems. I also have a strong background in physics and mathematics, with an in-progress Ph.D. in Applied Mathematics from the University of Colorado Denver and multiple publications in scientific journals. My mission is to use data and AI/ML to advance scientific discovery and social good.