Responsibilities

Develop, implement, and validate derivatives pricing models for new and existing products across various asset classes (e.g., equities, commodities, futures, perpetuals, options).
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.
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.