Risk Manager, Quantitative

About the role

This role involves owning and developing margin methodologies, including SPAN and VaR, and benchmarking them against established clearing house models. A key part of the work is to design, implement, and validate derivatives pricing models for various asset classes, ensuring they meet regulatory and audit standards through thorough backtesting and documentation.

The position requires building and maintaining data pipelines and automated reporting using SQL and Python, alongside monitoring real-time and historical portfolio risk metrics such as exposure and leverage. The manager will also be responsible for designing automated liquidation logic to manage market risk during volatile periods and performing scenario analysis.

Success in this role means providing critical risk input for product onboarding and regular parameter reviews, analyzing market microstructure, and continuously calibrating risk models to evolving market conditions. The manager will also contribute to the development and maintenance of internal risk dashboards and analytical tools.

The salary for this position ranges from $105,000 to $175,000 annually.

Skills that matter here

• Python: Used for building and maintaining data pipelines, automated reporting, and developing quantitative models.
• SQL: Essential for managing and querying relational databases to support risk models and reporting.
• risk management: Central to the role, involving the design, validation, and monitoring of risk models and methodologies.
• quantitative analysis: Applied to develop and validate derivatives pricing models and perform scenario analysis and stress testing.
• derivatives pricing: Crucial for developing and implementing models across various asset classes, including futures, perpetuals, and options.

Who this role suits

• A person with a Master's or PhD in a quantitative discipline.
• Someone with at least five years of experience in quantitative research, risk management, or trading.
• An individual with a deep understanding of derivatives pricing theory and order book dynamics.
• A candidate who thrives on critical thinking and continuous improvement in a fast-paced environment.

From the employer

• 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.

• 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.
• Strong understanding of derivatives pricing theory across traditional and digital asset classes.
• Deep understanding of Order Book Dynamics (L1-L3 data) and Cross/Portfolio-Margining methodologies (e.g., offsetting spot against futures).
• Deep knowledge of equities, commodity products, macro assets, and ongoing developments in these spaces; thoroughly familiar with futures, perpetuals, or other derivative types.
• Direct trading experience (personal or professional) is highly ideal, with a deep familiarity with margin concepts and liquidation mechanisms.
• Experience at a broker-dealer, exchange, or clearing organization, with familiarity on how brokers and CCPs operate is a strong plus.
• Think critically and strive for continuous improvement.

• Competitive salary
• Attractive annual leave entitlement including: birthday, work anniversary
• 401(k) plan with employer match
• Eligible for company-sponsored group health, dental, vision, and life/disability insurance
• Work Flexibility Adoption. Flexi-work hour and hybrid set-up
• Aspire career alternatives through us. Our internal mobility program can offer employees a diverse scope.