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Quantitative Methodology Expert
il y a 1 mois
About ENGIE Global Energy Management & Sales
ENGIE Global Energy Management & Sales (GEMS) is a leading energy supply solutions and risk management services provider, supporting clients through their decarbonization journey while optimizing ENGIE's assets and contributing to value creation.
With a global presence and 3,300 employees, GEMS offers a wide range of energy management services, including renewable and thermal power, natural gas & LNG, biomass, and environmental products. Our experts provide tailored solutions based on a wide range of energy management expertise, with a strong focus on decarbonation and decentralization.
Main Activities
As a Quantitative Methodology Expert, you will work on financial modeling and IT development, including:
- Financial modeling: Stochastic pricing models, XVA, VaR, SVaR, CVaR,...
- IT development: C#, Python, and big data (Amazon web service, Dataiku)
Pricing Model Validation
You will be in direct contact with traders and pricing model designers to understand derivatives and stochastic pricing models, challenge theoretical model design and measuring model risk, develop validated stochastic models in C#, and develop alternative stochastic models.
Market and Credit Risk Model Design
You will design XVA, VaR, SVaR, and CVaR models, improve stochastic models to implement in the risk engine, interact with the risk team and trading team to understand problems and propose solutions, develop and test models in Python, and work with the IT team for risk engine implementation.
Model Ongoing Monitoring
You will ensure model quality over time in a big data environment (Python + Amazon web service), challenge exotic parameters of pricing models, design, implement, and automate pricing model quality metrics, and calibrate stochastic model risk under historical probability.
Requirements
To succeed in this role, you will need:
- Knowledge of stochastic models applied to derivative pricing and risk modeling
- Knowledge of statistics (hypothesis testing, time series, regression analysis)
- Good object-oriented programming skills (C#, Python) to develop prototypes and models
- Knowledge of Amazon web service or other big data environments
- Some experience in commodity markets
Education/Seniority
You will need a university degree (Master or PhD) in Financial Engineering, Applied Mathematics, Statistics, Physics, Engineering, or Computer Sciences, and confirmed experience of at least 3 years as a quantitative analyst in pricing and risk modeling.
Language
Fluent in English.
