Quantitative Risk Analyst

ENGIE - International Supply & Energy Management; Brussel; Sur place; EUR 90 000 - 130 000; Plein temps

Résumé du poste

ENGIE is seeking a Quantitative Risk Analyst to validate pricing models for derivatives and to design robust risk models for market, credit, and liquidity risks.

You will implement stochastic models in C# within a pricing library and work with Big Data tools like AWS/Dataiku, collaborating with Risk, IT, and Front Office teams.

Qualifications

• You hold a Master’s degree or PhD in a quantitative discipline with a strong modeling foundation.
• You have 4–5 years of hands-on experience developing and validating pricing and risk models.
• You combine quantitative insight with practical software skills in C# and Python.

Responsabilités

• Validate pricing models for derivatives and design risk models for market, credit, and liquidity risks.
• Implement and test stochastic models in C# within a pricing library in a Big Data environment.
• Build alternative models, back-test prototypes, and contribute to model governance committees.
• Design risk metrics (VaR, SVaR, stress tests) and document methods for traceability.

Connaissances

Stochastic models

Statistics

C# / Python

Big Data (AWS/Dataiku)

Commodity markets

English & French

Formation

Master’s or PhD in quantitative discipline

Outils

Dataiku

AWS

Description du poste

Location: Bruxelles - Belgique

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 Analyst Pricing & Risk Model

Quantitative Risk Analyst – Risk Methodologies & Pricing Models

Location: Bruxelles - Belgique

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.

Context

The Global Business Unit Supply & Energy Management leverages ENGIE’s assets to deliver secure and sustainable energy to its B2B and B2C customers. It uses its expertise in energy management to provide decarbonized electricity 24/7.

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. Join us and be part of those shaping the energy of tomorrow!

As a Quantitative Risk Analyst

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

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. Beyond your studies, you bring at least four to five years of hands‑on experience as a quantitative analyst, during which you’ve developed, implemented, and challenged pricing and risk models in real‑world financial environments. You are now 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 and French

Why join us?

Diversity & Inclusion

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.

About ENGIE

ENGIE is a global leader in low-carbon energy and services, committed to accelerating the transition towards a carbon‑neutral world. Our purpose (“raison d’être”) is clear: act to reduce energy consumption and develop cleaner, more sustainable solutions that balance economic performance with a positive impact on people and the planet.

We rely on our core businesses — gas, power, renewable energy, and services — to deliver competitive, tailored solutions to our customers worldwide.

With 96,000 employees and a strong network of partners and stakeholders, ENGIE is more than a company: we are a community of Imaginative Builders, working every day to create harmonious, sustainable progress.

Business Unit: Supply & Energy Management

Division: EM RISK CONTROL

Entité légale: ENGIE GLOBAL MARKETS, BELGIAN BRANCH

Nom de l'entreprise: Supply and Energy Management

Salaire de base minimum:

Salaire de base maximum:

Base salariale: