Crypto Trading Advisor
Uses OpenAI-based LLM workflows to generate and evaluate trading recommendations across several timeframes, with monitoring to track how each signal performs.
Front office engineer building xVA pricing and risk simulation platforms in Python, C# and .NET. Lately: agentic AI and LLM tooling.
I'm a developer in front office technology. I build and support the platforms that price derivatives and simulate risk across global portfolios, working with portfolio managers, traders and quants in London, New York, Frankfurt and Hong Kong.
I got here the long way round. I studied English literature in Beijing, did an MSc at the LSE, co-founded an education venture, then spent five years teaching Mandarin and leading departments. In 2023 I finished the Code First Girls bootcamp with a distinction and moved into regulatory technology, then into xVA.
Teaching taught me to explain hard things simply, and that still shapes how I write code and work with desks. These days I'm most excited about AI-driven automation that works safely in a regulated environment.
Off the clock: travel, food and badminton.
Uses OpenAI-based LLM workflows to generate and evaluate trading recommendations across several timeframes, with monitoring to track how each signal performs.
An interactive network map of cryptocurrency wallets for spotting relationships and behaviour patterns, with graph analytics that scale to large transaction datasets.
Pulls prices automatically, runs them through ETL-style processing, and sends notifications through external APIs when a price moves.
A full-stack web app with user accounts, workout data processing and a database backend. Built during the Code First Girls bootcamp.
Open to chats about risk tech, AI automation in finance, or teaching people to code. I'm based in London.