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Quantitative Methodology Specialist
Il y a 2 mois
ENGIE Global Energy Management & Sales (GEMS) is a leading provider of energy supply solutions and risk management services. Our mission is to support our clients in their decarbonization journey while optimizing ENGIE's assets and contributing to value creation.
Our ExpertiseWe offer a wide range of services, including:
- Asset Management: We provide expert management of our clients' assets, ensuring optimal performance and value.
- Energy Transition Services: We help our clients navigate the transition to a low-carbon economy, providing innovative solutions and expertise.
- Energy Supply & Global Commodities: We offer a comprehensive range of energy supply solutions, including renewable and thermal power, natural gas & LNG, biomass, and environmental products.
- Risk Management & Market Access: We provide expert risk management services, including XVA, VaR, SVaR, and CVaR, to help our clients navigate complex markets.
We are seeking a highly skilled Quantitative Methodology Specialist to join our team. The successful candidate will be responsible for:
- Financial Modeling: Developing and implementing stochastic pricing models, XVA, VaR, SVaR, and CVaR.
- IT Development: Designing and developing C# and Python-based models and tools for risk management and financial analysis.
- Pricing Model Validation: Validating stochastic pricing models and challenging theoretical model design and measuring model risk.
- Market and Credit Risk Model Design: Designing and implementing XVA, VaR, SVaR, and CVaR models, and improving stochastic models for risk engine implementation.
- Model Ongoing Monitoring: Ensuring model quality over time, challenging exotic parameters, and designing, implementing, and automating pricing model quality metrics.
To be successful in this role, you will need:
- Knowledge of Stochastic Models: Applied to derivative pricing and risk modeling.
- Statistical Knowledge: Hypothesis testing, time series, and regression analysis.
- Programming Skills: Good object-oriented programming skills in C# and Python.
- Big Data Experience: Familiarity with Amazon Web Service or other big data environments.
- Commodity Markets Experience: Some experience in commodity markets would be an asset.
We are looking for candidates with a university degree in Financial Engineering, Applied Mathematics, Statistics, Physics, Engineering, or Computer Sciences, and at least 3 years of experience as a quantitative analyst in pricing and risk modeling.Language
Fluency in English is required.
