Tristan Murfitt is a Quantitative Technology Director in London with 10 years of experience building data-driven trading systems and digital-asset infrastructure. He combines hands‑on engineering in Python, Go and JS with quantitative research—designing systematic crypto market‑making, HFT strategies and deep learning models for price prediction. Tristan has led engineering teams and product delivery across institutional and startup settings (SIG, Elwood, Menai, Qube), shipping fault‑tolerant cloud pipelines, OMS/EMS platforms and production ML services. An active maintainer and contributor to open-source projects, he’s improved developer ergonomics in libraries like moment-range while bringing a strong focus on type safety and CI/CD. Notably, he founded a crypto trading firm that implemented distributed model optimisation and multi-exchange market‑making, demonstrating both entrepreneurial drive and production-scale ML/engineering chops.
10 years of coding experience
6 years of employment as a software developer
A Level Biology Geography Maths, A Level Biology Geography Maths at Sir Thomas Rich's Grammar School
1st Class BSc Computer Science w/ Industrial Year Computer Science Machine Learning, 1st Class BSc Computer Science w/ Industrial Year Computer Science Machine Learning at Loughborough University
Contributions:4 releases, 52 commits, 29 PRs in 1 year 11 months
Contributions summary:Tristan primarily contributed to the `moment-range` library by fixing linting errors and code formatting. They also implemented new features, such as adding `moment.rangeFromInterval()` and the `snapTo()` method. Furthermore, the user updated the project's type declarations and deprecated `parseZoneRange` in favor of `rangeFromISOString`, indicating maintenance and enhancement activities. These changes collectively improved the library's functionality, code quality, and developer experience.
Contributions:83 PRs, 133 pushes, 7 branches in 1 month
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