Senior Quantitative Analyst - Trading Risk & Fraud

Traze; Greater London; On-site; GBP 90,000 - 150,000; Full time

Job summary

Zeal Group through its Traze subsidiary seeks a Senior Quantitative Analyst to own the analytical backbone of trading risk and fraud. This hands-on role requires building systems to detect toxic flow, latency arbitrage, and abusive behavior, with autonomy and reporting to the Head of Risk.

The ideal candidate has ML/data science in financial markets and hands-on delivery experience across end-to-end analytics projects.

Qualifications

• 3+ years' experience in Quant/Trading or FX/CFD brokerage in a quantitative, risk, or analytics role.
• Hands-on experience with production-grade tools, dashboards, or systems.
• Strong knowledge of financial trading products and execution mechanics.
• Evidence of data science projects in financial markets.

Responsibilities

• Design, build, and maintain systems detecting toxic flow, latency arbitrage, and abusive trading patterns.
• Investigate, classify, and act on risk using the developed technology.
• Analyze trading products for fraud exposure and propose mitigations.
• Own end-to-end delivery from data extraction to production deployment.
• Mentor junior analysts as the function grows.

Skills

Quantitative analysis

Risk analytics

Independent work

Education

Bachelor's degree in Mathematics/Statistics/Physics/Finance

Tools

Python

SQL

Job description

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 Role

We 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.

The ideal candidate must have hands-on experience and strong foundation with machine learning and data science in financial markets.

Responsibilities

• Design and build the backend infrastructure, monitoring tools, and detection algorithms used to identify toxic flow, latency arbitrage, and abusive trading patterns
• Use the systems you build to investigate trading and non-trading activity, detect suspicious behavior, and report findings
• Analyze existing and new trading products and promotions for fraud/abuse exposure and propose mitigations
• Classify clients to support A-book/B-book decisioning and profitable execution outcomes
• Own end-to-end delivery: from raw data extraction and hypothesis testing through to production deployment of monitoring and alerting systems
• Continuously identify gaps in current processes and design new logic to increase automation and reduce manual intervention
• Mentor others on technical and analytical approaches as the function grows

Requirements

Must have

• 3+ years' experience in Quant/Trading OR FX/CFD brokerage environment, in a quantitative, risk, or analytics role
• Proficient experience with Python is mandatory.
• Demonstrated experience independently building and owning production-grade tools, dashboards, or systems (not just using existing ones)
• Can provide evidence of data science related projects, ideally end-to-end driven projects.
• Strong knowledge of financial trading products, trading conditions, and execution mechanics
• Understanding 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 field
• Comfortable working with high ownership and low supervision; proactive and self-directed

Preferred

• Experience with SQL.
• Experience or understanding of A/B-book risk models, transaction cost analysis, or execution analytics
• Exposure to regulatory reporting (MAR, FCA, CySEC, ASIC)
• Track record of mentoring junior analysts

This 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.