Summary
Zeal Group is hiring a Senior Quantitative Analyst to build and operate systems for trading risk and fraud detection. The role includes developing monitoring tools and algorithms, investigating suspicious trading activity, assessing product and promotion risks, and supporting client classification for execution decisions. Applicants should have at least 3 years of relevant quantitative, risk, analytics, trading, or FX/CFD brokerage experience, strong Python skills, and a degree in a quantitative field. The role is based in the United Arab Emirates; no salary or visa conditions are stated.
The posting
As published on zealgroup.global. Pulled from the employer's site and shown as they wrote it.
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.