Senior Quantitative Analyst - Trading Risk & Fraud

Zeal Group is an award-winning global FinTech powerhouse with 700+ professionals across London, Europe, Asia, MENA, and South America. Through our subsidiary Traze, we deliver advanced multi-asset trading solutions across Gold, Oil, FX, Indices, and Cryptocurrencies, built for today's fast-moving, high-volatility markets.About The RoleWe are looking for a Senior Quantitative Analyst to own the technical and analytical backbone of our trading risk and fraud function. This is a hands-on, individual-contributor role — not a management position. You will design, build, and maintain the systems that detect toxic flow, latency arbitrage, and abusive trading behavior, and you will use that technology yourself to investigate, classify, and act on risk. You'll report to the Head of Risk, working with a high degree of autonomy and minimal oversight.ResponsibilitiesDesign and build the backend infrastructure, monitoring tools, and detection algorithms used to identify toxic flow, latency arbitrage, and abusive trading patternsUse the systems you build to investigate trading and non-trading activity, detect suspicious behavior, and report findingsAnalyze existing and new trading products and promotions for fraud/abuse exposure and propose mitigationsClassify clients to support A-book/B-book decisioning and profitable execution outcomesOwn end-to-end delivery: from raw data extraction and hypothesis testing through to production deployment of monitoring and alerting systemsContinuously identify gaps in current processes and design new logic to increase automation and reduce manual interventionMentor others on technical and analytical approaches as the function growsRequirementsMust have5+ years' experience in a trading/FX/CFD brokerage environment, in a quantitative, risk, or analytics roleDemonstrated experience independently building and owning production-grade tools, dashboards, or systems (not just using existing ones)Strong knowledge of FX/CFD products, trading conditions, and execution mechanicsUnderstanding of fraud/abuse patterns in trading (toxic flow, latency arbitrage, manipulation)Bachelor's degree or higher in Mathematics, Statistics, Physics, Finance, or a related quantitative fieldComfortable working with high ownership and low supervision; proactive and self-directedPreferredExperience with Python and/or SQL for data analysis and system-buildingExperience with A/B-book risk models, transaction cost analysis, or execution analyticsExposure to regulatory reporting (MAR, FCA, CySEC, ASIC)Track record of mentoring junior analystsThis role suits someone who wants to build something from the ground up and use it, not just analyze data others have prepared. If you're a quant who thinks in systems, takes initiative without being asked, and wants ownership over a real risk function — this is built for you.