Quantitative Analyst Pricing

Join to apply for the Quantitative Analyst Pricing & Risk Model role at ENGIE - International Supply & Energy Management Location: Paris La Défense About ENGIE and Supply & Energy Management: ENGIE, a global leader in low‑carbon energy and services, relies on its Global Business Unit Supply & Energy Management (GBU S&EM) to provide reliable, sustainable, and affordable energy to all its customers. This strategic unit optimizes the Group’s and clients’ production assets and designs tailored energy solutions for our 200,000 professional clients and 15 million consumers. Quantitative Risk Analyst – Risk Methodologies & Pricing Models Location: Paris La Défense Joining Supply & Energy Management means becoming part of a team of over 10,000 passionate experts spread across 20 countries, all united by a shared mission: shaping a greener and more efficient energy future. Together, we push the boundaries of innovation to deliver decarbonized energy 24/7. Context As a Quantitative Risk Analyst, you will sit at the intersection of financial modeling, risk management, and software development. Your responsibilities 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: cultivate a critical mindset and challenge stochastic models through close interaction with traders and pricing model designers. Technical Development: 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: 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: You hold a Master’s degree or PhD in a quantitative discipline such as Financial Engineering, Applied Mathematics, Statistics, Physics, Computer Science, or a related field. You have at least three years of hands‑on experience as a quantitative analyst, developing, implementing, and challenging pricing and risk models in real‑world financial environments. You are looking to take on a new challenge where your expertise can make a real impact — bridging cutting‑edge theory with practical, high‑stakes applications in trading and risk management. 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. Why join us? At ENGIE S&EM, we are committed to fostering a gender‑neutral and inclusive environment where everyone’s potential can thrive. All our positions are open to people with disabilities. If you need any reasonable accommodations during the recruitment process, please inform your recruiter — we will be happy to support you. If you meet these requirements, then you are the talent we are looking for. Don’t wait – apply now with your CV. #J-18808-Ljbffr