Sean Mcowen is a quantitative strategist and research engineer with nine years of experience building data-driven investment systems, digital twins, and large-scale analytics pipelines across hedge funds, cryptocurrency projects, and academia. Currently VP and Senior Analyst in Systematic Credit at Acadian, he previously led engineering at BlockScience where he designed simulations for major cryptocurrencies and transformed 100+ TB of blockchain data into specialized AWS analytics databases. His background blends applied mathematics and analytics (MS from Columbia and Georgia Tech) with practical finance training (Finance/Econ BA), and he holds CAIA and FRM credentials while pursuing CFA Level III. Sean has a track record of turning complex numerical research—ranging from storm-surge neural networks to market-neutral strategy optimizers—into production systems and client-facing policy simulations, and he often bridges technical documentation with implementation for multidisciplinary teams. A not-obvious strength is his experience managing end-to-end products from research through automated execution and investor due diligence, making him as comfortable in code and cloud ops as in presenting strategy to clients.
9 years of coding experience
8 years of employment as a software developer
Master of Science - MS, Analytics - Computational Data Analytics Track, 3.70 GPA, Master of Science - MS, Analytics - Computational Data Analytics Track, 3.70 GPA at Georgia Institute of Technology
Master of Science - MS, Applied Mathematics, 3.96 GPA, Master of Science - MS, Applied Mathematics, 3.96 GPA at Columbia University in the City of New York
Bachelor's degree, Economics and Finance Double Major Math Minor, 3.70 GPA, Cum Laude, Bachelor's degree, Economics and Finance Double Major Math Minor, 3.70 GPA, Cum Laude at Boston College
Mathematical Specification for the Pocket Digital Twin
Contributions:38 PRs, 84 pushes, 36 branches in 2 months
mathspecpocket
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