Team
Keval D. Amin
ML/Web3 Developer · Stellar Development Foundation · Statistics & Economics · UC Berkeley – Sciences Po
Keval is a quantitative thinker and blockchain developer combining rigorous academic training in statistics, economics, and political science with hands-on ML and Web3 engineering experience — currently interning at SM Web Systems and building on prior work at the Stellar Development Foundation.
About Keval
Keval is currently a Blockchain Developer Intern at SM Web Systems (January 2026 – present), where he applies his ML and Web3 background to on-chain development. Prior to this he spent four months as an ML & Asset Quality Engineering Intern at the Stellar Development Foundation in Berkeley, CA — working at the intersection of machine learning, asset data quality, and blockchain infrastructure.
At Berkeley he has served as a Research Associate at Berkeley Economics and as a Consultant with the Behavioral Economics Association, bringing a causal inference and mathematical modelling lens to applied research questions. He is completing a dual BA in Statistics/Economics (UC Berkeley) and Politics and Government (Sciences Po), graduating in 2026.
Earlier in his career Keval worked in civic and humanitarian contexts — as a Civic Intern at Care4Calais in London and as Head of Events at Sciences GeoPo in Reims — alongside nearly five years as a Cadet Corporal in the Combined Cadet Force. He speaks English and Gujarati natively, French professionally, and has working knowledge of German and Hindi.
Focus Areas
- Blockchain development — Web3, Stellar, on-chain tooling
- Machine learning & asset quality engineering
- Quantitative methods — mathematical modelling, causal inference
- Behavioral economics research & applied consulting
How Keval Works With You
- Bridges ML and Web3 with depth on both sides — his Stellar internship put him at the exact intersection of machine learning and blockchain infrastructure, making him well-placed for data-intensive on-chain projects.
- Brings rigorous quantitative reasoning to engineering problems — a dual degree in statistics, economics, and political science means he approaches system design with the same tools used for causal inference and mathematical modelling.
- Operates across disciplines and cultures: multilingual (English, French, Gujarati) with experience spanning civic organisations, humanitarian work, and academic research — a communicator who can translate between technical and non-technical audiences.
Find Keval online
Listen to Keval's short audio introduction (coming soon).
Keval's detailed CV and LinkedIn export will appear here.