Quantitative Risk Manager

Role

Cross-product risk leadership

• Own risk and investigation strategy and ensure consistent methodology across product lines.
• Translate aggregate book intelligence into risk design, thresholds, and investigation priorities; set monitoring priorities and turn findings into business decisions.
• Benchmark trader behavior against market trends and competitor products; track developments in FX, CFD, futures, and crypto prop trading.
• Represent the department in cross-functional forums with product, technology, marketing, community, and partner stakeholders.

Team and investigations

• Lead investigation leads and senior analysts, setting performance standards, supervision routines, coaching, and career paths.
• Standardize the investigation playbook, escalation criteria, evidence standards, verdict frameworks, and communication protocols; document methods.
• Partner with HR and department leadership on hiring, calibration, and succession planning.

Risk framework and analytics

• Design abuse-detection architecture, risk parameters, and behavioral constraints across products.
• Run quantitative simulations and historical audits to calibrate risk filters while balancing firm capital protection and trader experience.
• Identify platform vulnerabilities and exploit patterns and recommend countermeasures.
• Drive automation, dashboard development, monitoring, alerting, and KPI maturity; provide evidence-backed input on rules, challenges, and platform configuration.

Experience and expertise

• At least 7 years in trading risk, brokerage risk, dealing, FCM/futures supervision, or trade surveillance, including at least 4 years in senior or leadership capacity.
• Dealing-desk experience with aggregate flow, book exposure, and population-scale trader behavior; track record leading investigation, surveillance, or risk analytics teams.
• Meaningful experience in both CFD/FX and futures markets; willingness and capability to extend into crypto.
• Advanced quantitative capability with Excel, SQL, Python/R, or equivalent, and ability to direct technical teams building analytics infrastructure.

Additional qualifications

• Strong judgment, integrity, decisive decision-making under pressure, and communication across teams and senior stakeholders.
• A degree in Computer Science, Statistics, Mathematics, or a risk-related field is preferred.
• Proprietary trading or trader evaluation experience, platform familiarity, BI tools, and AI tools for analytical work are listed as advantages.

Interview process