Daniel is the founder and principal of Manganese Solutions, an AI strategy consultancy focused on product-oriented machine learning and AI strategy and execution. He is a data science executive with over 8 years of experience leading teams at multiple companies, ranging from early stage startups to national organizations, including responsibility for multimillion dollar strategic initiatives.
Daniel holds a PhD in mathematics from Princeton University. He is an expert in machine learning and AI, with deep domain expertise in the healthcare and biotech spaces, including publications in prestigious academic journals.