Quantitative Analyst, Market Risk
Vitol is looking for a quantitative risk professional to join our Market Risk team, partnering directly with commercial teams to shape how we measure risk, price complexity, and allocate capital across a global commodities platform. This is a high-impact role for someone who enjoys building robust analytics, challenging assumptions, and translating quantitative insights into better trading and structuring decisions.
You’ll sit close to the business—working across portfolios and products (including options and structured exposures)—with the mandate to improve models, elevate risk transparency, and help the firm take intelligent risk.
What you’ll do
- Support portfolio-level risk insight across commodities: VaR, stressed VaR, stress testing, scenarios, tail-risk and concentration analysis.
- Partner with traders on complex deals—bringing rigor to payoff design, option modelling, hedging intuition, and risk/return assessment.
- Build and enhance models used in day-to-day risk taking (e.g., risk factor mapping, volatility and correlation dynamics, scenario generation, portfolio aggregation).
- Turn analytics into decisions: deliver clear narratives on risk drivers, convexity, carry, and what matters in adverse regimes.
- Drive improvements to tooling and data: help evolve internal risk systems, dashboards, and automated reporting with technology partners.
- Challenge and strengthen the framework: contribute to methodologies, limits, controls, and governance—raising the bar on model quality and explainability.
What makes this role different
- Real commercial proximity: your work influences decisions, not just reporting.
- Breadth + complexity: multi-commodity portfolios, options, and structured risk—where nonlinear exposures and tail events matter.
- Build, not just run: strong scope to modernize approaches (e.g., improved stress libraries, scenario design, model validation, and scalable analytics).
Qualifications
What we’re looking for
- Degree (BS/MS/PhD) in a quantitative discipline (Math/Stats/Physics/Engineering/CS/Finance or similar).
- Strong understanding of commodities and derivatives, including options and nonlinear risk.
- Demonstrated experience with VaR/stress testing/scenario analysis and the judgment to interpret them.
- Strong programming capability (typically Python; R/MATLAB also fine) and comfort working with large datasets.
- Ability to communicate clearly with senior stakeholders—turning technical outputs into actionable conclusions.
- Prior exposure to energy/commodities trading, particularly power and gas, is highly desirable
Additional (nice-to-have)
- Experience improving or owning methodologies (stressed VaR, scenario design, vol surface risk, correlation regimes).
- Hands-on contribution to risk platforms/tools in partnership with engineering.
- Track record of supporting structuring and complex transactions, particularly in power and gas markets.
Additional Information
All your information will be kept confidential according to EEO guidelines.