Quant Trading Analyst

About TMGM TMGM is at the forefront of the CFD trading industry, providing a comprehensive trading platform that includes stocks, commodities, indices, and currencies. We pride ourselves on fostering a culture of integrity, innovation, and excellence, ensuring our clients receive unparalleled trading experiences while strictly adhering to regulatory standards.

About the role You will join our highly experienced Systematic Market Making team, supporting the desk’s day-to-day operations through automation, data analytics, and reporting infrastructure development. This role sits at the intersection of trading, data engineering, and quantitative analytics. You will play a key part in ensuring the desk operates efficiently, with reliable reporting, clean data pipelines, and actionable insights derived from large volumes of trading and market data. You will work closely with Quant Traders, Risk Managers, and Developers, gaining exposure across pricing, hedging, liquidity management, and performance analysis. You will have a clear pathway to progress into leading the development of quantitative trading strategies.

Responsibility Trading Operations & Automation • Automate daily operational workflows across trading and risk functions. • Develop and maintain scripts to improve efficiency and reduce manual processes. • Support monitoring tools for pricing, hedging, exposure, and execution quality. • Improve robustness and reliability of trading-related systems.

Reporting Infrastructure & Data Systems • Design, develop, and maintain reporting frameworks for trading performance, risk exposure, and liquidity metrics. • Build scalable and maintainable data pipelines. • Ensure data integrity and accuracy across reporting systems. • Contribute to ad-hoc analysis requests from traders and senior management.

Data Analytics & Research Support • Transform raw trading and market data into structured, usable datasets. • Extract insights to support pricing optimization and hedging efficiency. • Analyze client flow, spread performance, slippage, and inventory behavior. • Assist in research projects by preparing and validating datasets.

Technology & Tools • Heavy use of Python for analytics, automation, and data processing. • Extensive use of SQL for querying large trading databases. • Work with time-series data across multiple asset classes (FX, Metals, Indices, Commodities, Single Stocks). • Continuously improve internal research and reporting tooling.