Stewart Douglas
Quantitative Researcher
England, United Kingdom
Summary
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Rockstar🎓
Top SchoolStewart Douglas is a quantitative researcher with 12 years of experience applying software engineering and data science to systematic investing, currently at Verition after five years as a quantitative developer at Marshall Wace. He blends production-grade Python back-end development—contributing to the well-known Zipline algorithmic trading library—with rigorous quantitative research, data engineering and trading-system design. His background spans consulting and entrepreneurship, giving him a pragmatic bent for translating business problems into testable models and reliable APIs. Trained in computing science and mathematics at Imperial, KCL and MIT with an economics undergraduate from Cambridge, he brings multidisciplinary rigor to model development and infrastructure. An unassuming but impactful contributor, he has improved date handling, error reporting and API testability in open-source quant tooling—small fixes that materially reduce operational risk in live trading.
12 years of coding experience
9 years of employment as a software developer
Visiting Student Mathematics and Computer Science, Visiting Student Mathematics and Computer Science at Massachusetts Institute of TechnologyMSc Computing Science, MSc Computing Science at Imperial College LondonBachelor of Arts (B.A.) Economics, Bachelor of Arts (B.A.) Economics at University of CambridgeGraduate Diploma Mathematics, Graduate Diploma Mathematics at King's College London
Github Skills (10)
pandas10
api10
python10
apidoc10
algorithmic-trading10
testing10
cryptocurrencies9
ui-testing7
trading7
test-framework7
Programming languages (2)
Github contributions (5)
quantopian/zipline
Jul 2015 - May 2016
Zipline, a Pythonic Algorithmic Trading Library
Role in this project:
Back-end Developer
Back-end DeveloperContributions:120 commits, 32 PRs, 135 pushes in 10 months
Contributions summary:Stewart's primary contributions involve enhancing the Zipline algorithmic trading library. They focused on adding and improving the functionality of the API, including allowing users to set symbol lookup dates. Furthermore, they addressed bugs related to date formats and improved error handling. The user implemented code changes to facilitate testing and documentation of the API methods.
algorithmic-trading-libraryalgorithmic-tradingpythontrading-botbacktesting-trading-strategies
StewartDouglas/EnigmaMachine
Nov 2013 - Sep 2016
Contributions:4 commits, 1 push in 2 years 10 months
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