Joseph Mulligan is a quantitative researcher and analyst with 11 years of experience bridging academic rigor and applied finance, currently working as a Research Analyst at Cubist Systematic Strategies. He holds a PhD track in Mathematics of Random Systems through an EPSRC CDT at Imperial College London with visiting research at Oxford, and a BSc in Financial Mathematics from University College Dublin with a study-abroad year at UC Berkeley. His background includes multiple quantitative internships at Qube Research & Technologies and early analyst roles at Credit Suisse, reflecting a steady progression from practitioner to researcher in systematic trading. Joseph combines strong mathematical modelling skills with hands-on market experience, contributing to strategy research and data-driven decision making. Based in London, he brings a collaborative mindset and persistence—traits hinted at by repeated returns to quant internships that deepened domain expertise. An underappreciated strength is his ability to translate advanced stochastic theory into practical models used in live research environments.
11 years of coding experience
3rd Year Study Abroad as part of BSc in Financial Mathematics at UCD, 3rd Year Study Abroad as part of BSc in Financial Mathematics at UCD at University of California, Berkeley
Doctoral Visiting Student, EPSRC CDT in Mathematics of Random Systems, Doctoral Visiting Student, EPSRC CDT in Mathematics of Random Systems at University of Oxford
Doctor of Philosophy - PhD, EPSRC CDT in Mathematics of Random Systems, Doctor of Philosophy - PhD, EPSRC CDT in Mathematics of Random Systems at Imperial College London
Bsc. (Hons) Financial Mathematics, Bsc. (Hons) Financial Mathematics at University College Dublin
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