OverviewTo strengthen our Quantitative & Model Risk team, we are looking for a Quantitative Risk Manager to advance the mathematical modelling of our key risk indicators and ensure that non‑linear effects and non‑price‑related risks are properly considered. Reporting to the Head of Quantitative & Model Risk, you will develop and implement key risk indicators used for market risk management, set up simulations for the future evolution of relevant risk factors, and contribute to model risk management by validating valuation models built by the Front Office.Your main responsibilitiesDeveloping and advancing key risk indicators that reflect all relevant risk factors for energy-related transactions, including price, volume and non‑linear effectsImplementing mathematical and statistical models for the purpose of measuring non-linear risks via full revaluationPerforming model validation for valuation models developed by the Front OfficeDesigning and maintaining consistent, correlated simulations of relevant risk factors (e.g. price and weather variables)Integration of the developed key risk indicators and models into the Alpiq risk infrastructure from a conceptual and technical perspective together with the teamYour profileMSc., ideally complemented by a Ph.D., in Mathematical Finance, Mathematics, or a related quantitative fieldAt least 2 years of relevant experience in building valuation models, risk models or similar quantitative frameworksStrong knowledge of stochastic calculusExperience in simulating price diffusionsPractical understanding of derivative pricingSolid programming experience in Python, including Pandas and NumPyKnowledge of relational database design, SQL and OracleExperience with GitLab or similar version control toolsKnowledge of power and gas markets and products and understanding of core risk management concepts is a plusExperience with machine learning concepts (e.g. neural networks, reinforcement learning) is an advantageYou appreciate working in a team of risk managers with different backgrounds
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