Home Jobs Quantitative Risk Analyst - Risk Methodologies & Pricing Models
Back to Jobs

Quantitative Risk Analyst - Risk Methodologies & Pricing Models - Job Opportunity at ENGIE Global Energy Management & Sales

Courbevoie, France
Full-time
Mid-level
Posted: May 29, 2025
On-site
EUR 70,000 - 95,000 annually based on the mid-level experience requirements, specialized quantitative skills in energy derivatives, and the strategic location in Courbevoie near Paris financial district. The role's combination of advanced modeling responsibilities, C# development capabilities, and energy market expertise typically commands premium compensation within the French quantitative finance market.

Benefits

Work-life balance preservation in a fast-paced energy trading environment
Exposure to cutting-edge Big Data technologies including AWS and Dataiku platforms
Professional development opportunities within a global energy management leader with 170,000+ employees
Access to diverse international business platforms across 20+ countries
Career advancement within ENGIE's comprehensive energy transition ecosystem
Collaborative work environment fostering innovation and breakthrough results

Key Responsibilities

Drive validation of complex derivative pricing models including exotic basket options, swing options, storage valuation, and renewable energy instruments to ensure robust risk assessment across energy commodity markets
Architect and implement sophisticated stochastic models in C# within enterprise-grade risk methodologies pricing libraries, directly impacting trading decisions and portfolio valuation accuracy
Engineer alternative modeling frameworks and benchmarking systems to stress-test existing valuation methods and enhance model robustness for multi-billion euro energy portfolios
Lead presentations to internal model committees providing theoretical justifications and numerical evidence for model implementations affecting strategic risk management decisions
Design comprehensive market risk metrics including Value-at-Risk, Stressed VaR, and quantitative stress testing frameworks that inform executive-level risk appetite and capital allocation decisions
Develop credit risk measurement systems including Potential Future Exposure, Credit Valuation Adjustment, and Debt Valuation Adjustment methodologies critical for counterparty risk management
Establish enterprise-wide documentation standards and audit trails ensuring regulatory compliance across European energy markets and supporting ENGIE's risk governance framework

Requirements

Education

Master's degree or PhD in a quantitative discipline such as Financial Engineering, Applied Mathematics, Statistics, Physics, Computer Science, or a related field

Experience

At least three years of hands-on experience as a quantitative analyst

Required 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) Ability to independently develop models and prototypes Familiarity with Big Data technologies, particularly Amazon Web Services (AWS) or Dataiku Previous experience in Commodity Markets 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 Fluent in English
Advertisement
Ad Space

Sauge AI Market Intelligence

Industry Trends

Energy markets are experiencing unprecedented volatility driven by geopolitical tensions, renewable energy integration, and carbon pricing mechanisms, creating significant demand for sophisticated risk modeling capabilities that can handle complex energy derivative instruments and multi-commodity portfolios. The transition to net-zero emissions is fundamentally reshaping energy trading strategies, requiring quantitative analysts who can model renewable energy volatility, storage optimization, and green certificate valuations. Financial institutions and energy companies are increasingly investing in advanced analytics and machine learning capabilities to enhance their risk management frameworks, particularly in areas of climate risk modeling, ESG integration, and stress testing under extreme weather scenarios. This technological evolution demands professionals who can bridge traditional quantitative finance with emerging sustainability metrics and carbon accounting methodologies. Regulatory frameworks across European energy markets are becoming more stringent, with enhanced capital requirements, margin rules, and climate-related financial disclosures driving demand for robust model validation, back-testing capabilities, and comprehensive documentation standards that can withstand regulatory scrutiny and support strategic decision-making processes.

Role Significance

Typically operates within a specialized quantitative risk team of 8-15 professionals, collaborating closely with front office traders, IT development teams, and senior risk management executives. The role involves cross-functional interaction with multiple departments and may include mentoring junior analysts while reporting to senior quantitative risk managers or heads of model validation.
This mid-level position carries significant strategic influence within ENGIE's risk management framework, with direct impact on model validation decisions affecting multi-billion euro energy portfolios and trading strategies. The role combines technical expertise with business acumen, requiring independent judgment on complex derivative pricing models and direct communication with senior stakeholders including traders, model committees, and regulatory bodies.

Key Projects

Implementation of next-generation energy derivative pricing models incorporating renewable energy volatility, storage optimization algorithms, and carbon pricing mechanisms to support ENGIE's transition to low-carbon energy solutions Development of comprehensive stress testing frameworks that can simulate extreme market scenarios including energy supply disruptions, regulatory changes, and climate-related financial risks across diverse geographical markets Design and validation of sophisticated credit risk models for energy counterparties, including utilities, renewable energy developers, and industrial clients, incorporating ESG factors and transition risk assessments

Success Factors

Deep expertise in energy market dynamics and derivative instruments, particularly the ability to understand complex energy commodity structures including swing options, storage valuation, and renewable energy certificates, which are critical for developing accurate pricing models in ENGIE's diverse energy portfolio management operations. Strong programming capabilities in C# and Python with experience in big data environments, enabling the implementation of sophisticated models within enterprise-grade systems and the ability to prototype innovative solutions that can be seamlessly integrated into existing risk management infrastructure. Excellent communication skills for presenting complex quantitative concepts to diverse stakeholders including traders, senior management, and regulatory bodies, ensuring that model validation findings and risk metrics are clearly understood and actionable for strategic decision-making processes. Regulatory awareness and documentation excellence to ensure compliance with evolving European energy market regulations and internal governance standards, supporting ENGIE's position as a leading energy management company in highly regulated markets.

Market Demand

High demand driven by the critical intersection of energy transition, regulatory compliance, and advanced risk management capabilities required for navigating volatile energy markets and implementing sophisticated derivative pricing models in a rapidly evolving industry landscape.

Important Skills

Critical Skills

Stochastic modeling expertise is absolutely essential as this role involves validating and implementing complex derivative pricing models for energy instruments including exotic options, swing contracts, and storage facilities. These models directly impact trading decisions and risk assessment for multi-billion euro portfolios, requiring deep understanding of mathematical finance, probability theory, and numerical methods specific to energy market dynamics. Programming proficiency in C# and Python is critical for implementing validated models within enterprise-grade systems and developing prototypes for new risk metrics. The ability to write robust, maintainable code that integrates with existing infrastructure is essential for translating theoretical models into practical risk management tools that support daily trading operations and strategic decision-making. Energy market knowledge is indispensable for understanding the unique characteristics of energy derivatives, including seasonality patterns, storage constraints, transmission limitations, and regulatory impacts that distinguish energy commodities from traditional financial instruments. This expertise enables effective model validation and ensures risk metrics accurately reflect the complexities of energy market dynamics.

Beneficial Skills

Experience with cloud computing platforms and big data technologies enhances the ability to implement scalable risk management solutions and leverage modern data processing capabilities for advanced analytics and real-time risk monitoring across global energy portfolios Regulatory knowledge of European energy market frameworks provides valuable context for model validation requirements, compliance standards, and governance processes that support ENGIE's operations across multiple jurisdictions and ensure adherence to evolving regulatory expectations Climate risk modeling expertise becomes increasingly valuable as energy markets integrate ESG considerations, carbon pricing mechanisms, and transition risk assessments into traditional financial risk management frameworks, supporting ENGIE's leadership in sustainable energy solutions

Unique Aspects

Direct involvement in cutting-edge energy transition modeling including renewable energy derivatives, carbon pricing mechanisms, and storage optimization algorithms that are reshaping global energy markets and supporting the worldwide shift toward sustainable energy systems
Access to ENGIE's vast and diverse energy asset portfolio spanning multiple countries, technologies, and market segments, providing unparalleled exposure to complex energy market dynamics and sophisticated risk management challenges across the entire energy value chain
Integration of advanced Big Data technologies including AWS and Dataiku platforms within energy trading operations, representing the convergence of traditional quantitative finance with modern data science capabilities in mission-critical energy market applications
Opportunity to contribute to regulatory compliance and model governance frameworks that support one of the world's largest energy transition initiatives, directly impacting global decarbonization efforts and sustainable energy development strategies

Career Growth

Progression to senior individual contributor roles typically occurs within 2-3 years, with advancement to management positions possible within 4-6 years based on demonstrated expertise in energy markets, leadership capabilities, and successful delivery of strategic risk management initiatives.

Potential Next Roles

Senior Quantitative Risk Analyst or Principal Risk Analyst positions within ENGIE or other major energy trading companies, focusing on advanced model development and team leadership responsibilities across global energy markets Head of Model Validation or Risk Methodology Manager roles, overseeing comprehensive model governance frameworks and leading teams of quantitative professionals in developing next-generation risk management capabilities Front Office Quantitative Analyst or Structuring roles, leveraging deep risk modeling expertise to support energy derivative structuring, trading strategy development, and client solution design within energy transition financing

Company Overview

ENGIE Global Energy Management & Sales

ENGIE Global Energy Management & Sales represents one of Europe's largest and most sophisticated energy trading and risk management operations, managing diverse energy portfolios across renewable and thermal power, natural gas, LNG, and environmental products. With over 3,300 employees operating through 20+ international business platforms, GEMS has established itself as a critical component of ENGIE's broader energy transition strategy, leveraging 20+ years of asset management expertise to serve 120,000+ clients spanning the entire energy value chain.

ENGIE maintains a dominant position in European energy markets and holds significant global presence in energy management services, ranking among the top energy trading houses worldwide with particular strength in renewable energy integration, natural gas trading, and carbon markets. The company's focus on decarbonization and energy transition positions it at the forefront of industry transformation, managing substantial trading volumes and providing critical risk management services to diverse energy market participants.
The Courbevoie location positions this role at the heart of European energy trading activities, with direct access to major energy exchanges, regulatory bodies, and key market participants. This strategic location enables close collaboration with European energy markets, regulatory authorities, and provides networking opportunities within the broader financial services ecosystem surrounding Paris.
ENGIE's culture emphasizes innovation, sustainability, and collaborative problem-solving within a global organization committed to energy transition and carbon neutrality. The work environment balances technical excellence with practical application, encouraging breakthrough results while maintaining work-life balance, and fostering professional development within a diverse, international team structure focused on meaningful environmental and economic impact.
Advertisement
Ad Space
Apply Now

Data Sources & Analysis Information

Job Listings Data

The job listings displayed on this platform are sourced through BrightData's comprehensive API, ensuring up-to-date and accurate job market information.

Sauge AI Market Intelligence

Our advanced AI system analyzes each job listing to provide valuable insights including:

  • Industry trends and market dynamics
  • Salary estimates and market demand analysis
  • Role significance and career growth potential
  • Critical success factors and key skills
  • Unique aspects of each position

This integration of reliable job data with AI-powered analysis helps provide you with comprehensive insights for making informed career decisions.