Teams at Graviton Research Capital LLP

Develop and enhance high-frequency trading strategies by analyzing financial data, building predictive models, and identifying market opportunities. Responsibilities include analyzing production trades, creating monitoring and post-trade systems, writing scalable C++ and Python scripts for risk and performance analysis, developing centralized market data tools, and supporting trading-system deployments. The role requires strong quantitative reasoning, programming skills, and familiarity with Linux, with high-frequency trading and low-latency experience preferred.

Conduct quantitative research for systematic trading by analyzing market data, formulating and testing hypotheses, developing statistical and machine learning models, backtesting strategies, studying market microstructure, and partnering with technologists to deploy production-ready research and trading systems.

Develop and maintain quantitative market risk models, stress tests, and scenario analyses using high-frequency trading data. Design position, P&L, and exposure limits; manage governance, approvals, alerts, and escalations. Produce intraday and daily risk reports, analyze post-trade risk and drawdowns, and support capital allocation. Collaborate with quantitative researchers, technology, compliance, and regulatory teams on risk infrastructure and exchange-rule adherence.