Energy Markets Quantitative Risk Analyst

ENGIE Group; Brussel; Sur place; EUR 70 000 - 110 000; Plein temps

Résumé du poste

ENGIE is seeking a Quantitative Risk Analyst to join its Supply & Energy Management team in Brussels. You will validate pricing models for derivatives and design risk models for market, credit, and liquidity risks using C# and Python in a Big Data setup (AWS, Dataiku).

You will collaborate with Risk, IT, and Front Office to deliver practical pricing tools, back-testing prototypes, and monitoring systems, combining rigorous theory with real-world trading risk.

Qualifications

• Master’s or PhD in a quantitative field with 4–5 years in quantitative analysis.
• Experience building and challenging pricing and risk models in real-world settings.
• Proficient in C# and Python for model development.
• Solid knowledge of stochastic models for pricing and risk.
• Fluent in English and French.

Responsabilités

• Validate pricing models for 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 valuation methods.
• Participate in internal model committees with theoretical and numerical justifications.
• Design risk metrics for market and credit risks; implement prototypes and IS integration specs.
• Ensure full documentation of models for traceability, auditability, and regulatory compliance.

Connaissances

Stochastic models

Derivatives pricing

Risk modeling

Statistics

C#

Python

Big Data

Formation

Master’s or PhD in a quantitative discipline

Outils

AWS

Dataiku

Description du poste

ENGIE is seeking a Quantitative Risk Analyst to join its Supply & Energy Management team in Brussels. You will validate pricing models for derivatives and design risk models for market, credit, and liquidity risks using C# and Python in a Big Data setup (AWS, Dataiku).

You will collaborate with Risk, IT, and Front Office to deliver practical pricing tools, back-testing prototypes, and monitoring systems, combining rigorous theory with real-world trading risk.