Sian Xiao is a quantitative strategist at Goldman Sachs Prime Risk with a decade of technical experience bridging computational chemistry and finance. She holds a PhD in Theoretical and Computational Chemistry from SMU and is concurrently pursuing an MS in Computer Science at Georgia Tech, combining rigorous modeling, ML, and deep learning to tackle complex, real-world problems. Her academic work focused on protein dynamics, conformation exploration, and allostery, applying MD, QM, and data-driven methods—skills she now translates to risk stratification and quantitative tooling. A former graduate instructor, she brings clear communication and pedagogy to cross-functional teams. Outside work, she codes, designs games, photographs, and is a certified private pilot and competitive marksman, reflecting a blend of creativity, precision, and discipline. Based in Dallas, she uniquely pairs high-impact research pedigree with practical engineering and product-minded delivery.
10 years of coding experience
5 years of employment as a software developer
Polymer/Plastics Engineering, 3.88/4.0, Polymer/Plastics Engineering, 3.88/4.0 at The University of Akron
Bachelor of Engineering - BE, Polymer Materials and Engineering, 88/100, Bachelor of Engineering - BE, Polymer Materials and Engineering, 88/100 at Beijing University of Chemical Technology
High School Diploma, High School Diploma at Yangzhou High School of Jiangsu Province
Master of Science - MS, Computer Science, 3.9/4.0, Master of Science - MS, Computer Science, 3.9/4.0 at Georgia Institute of Technology
Doctor of Philosophy - PhD, Theoretical and Computational Chemistry, 4.0/4.0, Doctor of Philosophy - PhD, Theoretical and Computational Chemistry, 4.0/4.0 at Southern Methodist University
Contributions:40 PRs, 33 pushes, 3 branches in 2 years
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