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Risk Manager, Quantitative (EMEA)
Crypto.com
Dubai, UAE
Full-time
Manager · 5+ years experience
Hybrid
Discovered 1 weeks ago
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Responsibilities
- Own margin methodology across the group, including SPAN, VaR, and portfolio-margining approaches, and benchmark our models against those used by the clearing houses and exchanges we face.
- Develop, implement, and validate derivatives pricing models for new and existing products across various asset classes (e.g., equities, commodities, futures, perpetuals, options).
- Backtest margin coverage and document model performance, assumptions, and limitations to a standard that withstands regulatory and audit review.
- Build and maintain the data pipelines and automated reporting behind the risk models, working in SQL, Python, and relational databases.
- Monitor and analyze real-time and historical portfolio risk, including exposure, leverage, margin utilization, concentration, and liquidation.
- Design optimal automated liquidation logic and algorithms to balance market risk with market impact during extreme volatility.
- Perform scenario analysis and stress testing across a range of market conditions.
- Provide risk input into product onboarding, listing reviews, and regular risk parameter reviews: haircuts, margin levels, liquidation thresholds, index pricing, funding rates, and position limits.
- Analyze market microstructure on multi-asset derivative markets, periodically review and calibrate risk models according to evolving market conditions.
- Support the build and maintenance of internal risk dashboards and analytical tools.
Requirements
- 5+ years of relevant working experience in quantitative research, risk management, trading, or a related field. Exposure to daily risk operations is expected alongside the modelling work; regulator-facing experience is welcome but not required.
- Master or PhD in a quantitative discipline (e.g., math, physics, statistics, engineering, computer science, financial engineering, quantitative finance, etc.).
- Proficient in Python and SQL or noSQL data structures, data models, and database management.
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