Role:

As a Forecasting Team Member, you will contribute to the development and delivery of forecasting processes and models that support the energy supply business. Working under the guidance of the Forecasting Local Leader, you will collaborate closely with portfolio managers, pricers, and other business stakeholders to ensure forecasting outputs are accurate, timely, and aligned with operational needs. Your work will be based on rigorous data collection and analysis, and will directly contribute to optimizing costing, forecasting, sourcing, and hedging strategies within a defined business mandate.

You will be actively involved in the design, implementation, and continuous improvement of forecasting tools and methodologies, ensuring alignment with global standards and contributing to their evolution. Your role will also include cross-functional collaboration within the SPM community and with forecasting teams in other countries to promote knowledge sharing and consistency.

You will be responsible not only for the technical development of forecasting solutions but also for ensuring their operational reliability and relevance to business needs. This includes representing the dynamics of supply portfolios—such as commercial position evolution, climatic impacts on consumption forecasts, and customer behavior analysis—and supporting the development of new commercial offers.

In addition to model development, you will provide scientific expertise for bespoke analyses and contribute to the continuous improvement of forecasting practices. A solid understanding of energy market design (B2C and B2B regulation, sourcing mechanisms, and supply reliability) is essential to successfully carry out these missions.

Key Responsibilities :

• Model and Process Development: Contribute to the design, implementation, and continuous improvement of forecasting tools, models, and processes used to support the energy supply business.

• Portfolio Representation: Support the accurate representation of all commodity exposures and associated risks—including commercial position evolution, climatic impacts on short-term consumption forecasts, and customer behavior patterns.

• Commercial Offer Support: Participate in the development of forecasting components for new commercial offers, ensuring alignment with business needs and market dynamics.

• Customer Insights: Analyze customer behavior using diverse data sources to enhance forecasting accuracy and business relevance.

• Operational Execution: Ensure the reliable execution (“run”) of forecasting models and associated operations, maintaining consistency and quality in outputs.

• Portfolio Structuring: Provide business with deep insights into their commodity sales portfolios (Natural Gas, Power, and Certificates), and contribute to the optimal structuring of portfolio representations.

• Data Utilization: Leverage a wide range of internal and external data sources to ensure robust and accurate portfolio and consumption representation.

• Best Practices Promotion: Advocate for good practices in data handling, model development, and coding standards across the team and broader community.

• Code Quality Assurance: Ensure high-quality, maintainable code by adhering to established development standards and guidelines.

• Cross-Team Collaboration: Actively engage with other quantitative analysts and data scientists across teams to exchange ideas, models, data, and technical insights, fostering a collaborative and innovative environment.

Hard skills:

• Strong scientific background in mathematics (including probability and statistics), data science, and machine learning, with practical experience in time series forecasting.

• Proficient programming skills, in Python and R, with familiarity in software development best practices including version control (e.g., Git).

• Hands-on approach to data handling and operational analytics, with a focus on delivering practical, business-relevant solutions.

• Ability to simplify complexity, with strong communication skills to explain technical concepts and model outputs to non-experts in a clear and pedagogical manner.

• Interest in energy markets and energy transition topics, with a willingness to deepen understanding of market design and regulatory frameworks.

• Understanding of energy supply business processes and local market design is a big plus.

• Knowledge of modern data science platforms and engines, such as Databricks and Spark, is a strong asset.

• Experience with cloud-based analytics environments and digital tools used in forecasting and portfolio management.

Soft skills:

• Strong analytical mindset, with the ability to tackle complex forecasting challenges and translate data into actionable insights for the energy supply business.

• Clear and effective communication skills, especially in explaining technical concepts to both technical and non-technical stakeholders, including portfolio managers and pricers.

• Collaborative and inclusive team player, contributing to a positive and high-performing work environment.

• Creative and innovation-driven, with a passion for developing state-of-the-art forecasting models and solutions that push boundaries and anticipate future business needs.

• Agile and adaptive mindset, embracing continuous improvement, iterative development, and responsiveness to changing business priorities.

• Cultural intelligence, with the ability to work effectively in a multicultural and international environment, respecting diverse perspectives.

• Willingness to travel occasionally and engage with global forecasting teams.

Education and professional background:

• Master’s degree or PhD in applied mathematics, engineering, data science, physics, economics, or a related quantitative field

• 2+ years of experience in forecasting, data science, or quantitative analysis, preferably in the energy sector.

Languages:

• English is a must

• Other languages are welcome