Quantitative Analyst Pricing & Risk Model

Location

Paris La Défense

Position Overview

Quantitative Risk Analyst – Risk Methodologies & Pricing Models at ENGIE’s Supply & Energy Management (GBU S&EM).

Context

As a Quantitative Risk Analyst, you will be part of a team 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.

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 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. Your academic background has equipped you with a solid foundation in modeling, analytics, and problem‑solving. You have at least three years of hands‑on experience as a quantitative analyst, during which you have developed, implemented, and challenged 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

EEO Statement

ENGIE S&EM is 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.