Quantitative Risk Analyst

**Quantitative Risk Analyst - Risk Methodologies & Pricing Models** **ABOUT US (GEMS)** ENGIE Global Energy Management & Sales (GEMS) provides energy supply solutions and risk management services to support its clients through their decarbonization journey, while optimizing ENGIE’s assets and contributing to value creation. ENGIE is a global reference in low-carbon energy and services with a leading energy management business, piloted by its entity "Global Energy Management & Sales" who built its savoir-faire managing the Group’s large and diverse asset portfolio over 20+ years. 3,300 employees around the world develop our solutions, through +20 international business platforms. We cover the full energy mix: renewable and thermal power, natural gas & LNG, biomass, environmental products. Our experts provide tailor made solutions based on a wide range of savoir-faire in energy management with a strong focus on decarbonation and decentralization. Our +120,000 clients span the entire value chain: producers, asset developers, financial players, utilities, distributors and industrials. Our global reach and strong local presence enable us to offer these diverse clients tailor-made services and respond to rapid changes in mature or emerging markets alike. Our 4 expertise: - Asset management - Energy transition services - Energy supply & global commodities - Risk management & market access At GEMS we encourage breakthrough results, team spirit, curiosity and innovation while preserving the right work/life balance for you. **MISSIONS**: As a Quantitative Risk Analyst, you will be part of a team that sits at the intersection of financial modeling, risk management, and software development. Your responsibilities will include validating pricing models for derivatives and designing and continuously improving risk models for market, credit, and liquidity risks. Your daily tasks will encompass three key areas: - **Advanced Financial Modeling**: You will cultivate a critical mindset and challenge stochastic models through close interaction with traders and pricing model designers. - **Technical Development**: You will implement and test models and their alternatives within a robust C# and Python codebase, integrated into a Big Data environment (AWS, Dataiku). - **Cross-Functional Collaboration**: You will work closely with Risk, IT, and Front Office teams to transform complex problems into practical solutions, whether through ad hoc pricing tools, back-testing prototypes, or automated model monitoring systems. Additionally, you will ensure the long-term robustness of models by calibrating reserves under historical probability, implementing performance metrics, and regularly reviewing model parameters. This role combines scientific rigor with technical creativity and places you at the heart of the risk management team, focusing on energy commodity markets. **_Key responsibilities : _** - Perform model validation of pricing models for complex derivatives (e.g., exotic basket options, swing options, storage, renewables,). - Implement validated stochastic models in C# within the risk methodologies pricing library. - Build and test alternative models to benchmark and assess the robustness of valuation methods. - Participate in internal model committees by providing theoretical and numerical justifications. - Design risk metrics for market risks (VaR, SVaR, quantitative stress tests), implement prototypes and present method specifications for future IS integration. - Design risk metrics for credit risks (PFE, CVA, DVA), implement prototypes and present method specifications for future IS integration.Ensure full documentation of models and methods for traceability, auditability, and regulatory compliance.**PROFILE**: **_Hard Skills : _** - Solid knowledge of stochastic models applied to derivative pricing and risk modeling. - Strong background in statistics: hypothesis testing, time series analysis, regression models. - Proficient in object-oriented programming (C#, Python), with the ability to independently develop models and prototypes. - Familiarity with Big Data technologies, particularly Amazon Web Services (AWS) or Dataiku, is a plus.Previous experience in Commodity Markets is a strong advantage.**_Soft Skills : _** - Strong analytical skills, conceptual thinking, and scientific rigor. - Ability to communicate complex concepts clearly and effectively to both technical and non-technical stakeholders.Team spirit and ability to work collaboratively in a fast-paced and multidisciplinary environment.**LANGUAGES**: - Fluent in English **ABOUT ENGIE** Our group is a global reference in low-carbon energy and services. Our purpose (“raison d’être”) 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, rene