Quantitative Methodology Expert
il y a 4 semaines
About ENGIE Global Energy Management & Sales
ENGIE Global Energy Management & Sales (GEMS) is a leading energy supply solutions provider and risk management services company. Our team of experts helps clients navigate their decarbonization journey while optimizing ENGIE's assets and contributing to value creation.
We have a global presence with 3,300 employees across 20+ international business platforms, covering the full energy mix: 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.
Our clients span the entire value chain: producers, asset developers, financial players, utilities, distributors, and industrials. We offer diverse clients tailor-made services and respond to rapid changes in mature or emerging markets alike.
Main Activities
As a Quantitative Methodology Expert, you will work on financial modeling and IT development:
- Financial modeling: Stochastic pricing models, XVA, VaR, SVaR, CVaR,...
- IT development: C#, Python, and big data (Amazon web service, Dataiku)
Pricing Model Validation
- 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#;
- Develop alternative stochastic models in C#.
Market and Credit Risk Model Design
- XVA, VaR, SVaR, and CVaR model designer;
- Improve stochastic models to implement in the risk engine;
- Interact with the risk team and trading team to understand the problem and propose theoretical and technical solutions;
- Develop and test models in Python;
- Work with the IT team for risk engine implementation;
- Develop 'ad hoc' pricing tools and prototypes used by the FO, leveraging the pricing library and potentially developing customized tools.
Model Ongoing Monitoring
In a big data environment (Python + Amazon web service), ensure model quality over time:
- Challenge exotic parameters of pricing models;
- Design, implement, and automate pricing model quality metrics;
- Calibrate stochastic model risk under historical probability.
Requirements
- 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 would be appreciated;
- Some experience in commodity markets would be appreciated.
Soft Skills
- Analyzing complex problems, conceptual thinking, and rigor;
- Ability to explain and convey messages about complex issues;
- Working together, ability to work in a collaborative environment.
Education/Seniority
- University degree (Master or PhD) in Financial Engineering, Applied Mathematics, Statistics, Physics, Engineering, or Computer Sciences;
- Confirmed experience of at least 3 years as a quantitative analyst in pricing and risk modeling.
Languages
- Fluent in English.
About ENGIE
Our group is a global reference in low-carbon energy and services. Our purpose is to act to accelerate the transition towards a carbon-neutral world, through reduced energy consumption and more environmentally-friendly solutions, reconciling economic performance with a positive impact on people and the planet. We rely on our key businesses (gas, renewable energy, services) to offer competitive solutions to our customers. With our 170,000 employees, our customers, partners, and stakeholders, we are a community of Imaginative Builders, committed every day to more harmonious progress.
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