Daniel Huang is a web developer and product-minded technologist with 10 years of experience building data-driven products across cybersecurity, EdTech, and Web3. He blends a research background in economics and machine learning from UC Berkeley and UCLA with hands-on engineering—leading teams to ship AI-driven fraud detection APIs, scalable microservices on AWS, and full-stack education platforms. As a founder and consultant he has taken products from discovery to revenue, identifying large market opportunities (e.g., a $500M+ NFT fraud detection segment) and turning them into funded MVPs. He excels at unblocking teams and translating quantitative research into practical product features, having trained early-career engineers and led cross-functional squads. Based in Pleasanton, CA, Daniel pairs entrepreneurial grit with rigorous experimentation—equally comfortable prototyping in React/Django as running customer interviews and quantitative market analysis.
10 years of coding experience
7 years of employment as a software developer
Master of Development Engineering - MDE, AI/Data Science, Master of Development Engineering - MDE, AI/Data Science at University of California, Berkeley
Economics, Junior, Economics, Junior at International Christian University
Bachelor of Arts (B.A.), Economics, Bachelor of Arts (B.A.), Economics at University of California, Los Angeles
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