Senior Data Scientist

At ENGIE’s Global Business Unit Supply & Energy Management (GBU S&EM), the Senior Data Scientist - Data Modeling & Quality role sits within the TrueWatts domain of Supply Portfolio Management (SPM), a function focused on modeling and hedging energy risks for client portfolios.

ENGIE’s Global Business Unit Supply & Energy Management provides reliable, sustainable, and affordable energy to customers by optimizing production assets and designing tailored energy solutions. The unit serves 200,000 professional clients and 15 million consumers.

Our Mission & Objectives

• Deliver carbon-free energy to clients around the world, 24/7
• Maximize the value of ENGIE’s diverse assets—including renewables, thermal generation, and storage
• Serve over 15 million residential customers and 200,000 businesses, aiming to reach 550 TWh by 2030 with a growing share of green electricity
• Promote agility, collaboration, and transparency throughout the organization

S&EM is structured around three core pillars:

• OneB2B: Focused on streamlining and scaling ENGIE’s business-to-business solutions across multiple countries
• OneB2C: Dedicated to business-to-consumer operations
• Energy Management: Overseeing the optimization and risk management of energy assets and portfolios

OneB2B is a key pillar that drives ENGIE’s B2B strategy by accelerating the delivery of tailored solutions, reducing operational costs, and leveraging unified platforms and shared tools.

Within SPM, the TrueWatts transversal domain brings together experts in actual consumption management, shares best practices, builds expertise in data modeling and grid error management, and designs MPD features while supporting their deployment. MPD is the product responsible for metering data management at ENGIE.

This domain includes several operational Middle Offices responsible for certifying actual consumption volumes for balancing and billing across all Supply processes using MPD.

The core product team is a small data science team responsible for designing core features that are later industrialized by MPD IT teams. These features address grid data imperfections such as gaps in time series and inconsistencies between sources. The team develops the common framework used across ENGIE’s B2B countries, from inconsistency detection to correction algorithms.

About the TrueWatts Team within SPM

The TrueWatts domain is a cross-functional team dedicated to actual consumption management. Its mission is to bring together experts from dedicated Middle Offices to certify actual consumption volumes for balancing and billing across every Supply process.

The TrueWatts domain plays a central role in designing and deploying the MPD metering data management product for ENGIE. It supports implementation by developing features and sharing best practices across operational Middle Offices.

At the core of TrueWatts is a focused data science team that creates and refines the foundational algorithms powering the MPD curation pack. The team addresses challenges such as gaps in time series data, inconsistencies between sources, and grid data imperfections. Its work spans detecting inconsistency patterns and building correction algorithms, establishing a framework applied across ENGIE’s B2B operations.

Joining TrueWatts means contributing directly to energy data reliability and helping shape green and competitive offers.

Role

As senior data scientist in the core business team of the TrueWatts domain, you will:

• Identify and analyze patterns of inconsistencies across the various available data sources.
• Develop and implement algorithms to correct detected inconsistencies.
• Design and deploy operational quality monitoring dashboards for use by Middle Offices.
• Work daily to enable Middle Offices to effectively fulfill their responsibilities across different Supply processes, including forecasting, pricing, billing, closing, and customer care.
• Support the industrialization of data processing solutions developed by the business team in collaboration with IT teams.

Hard skills

Data Platforms & Environment

• Expert command of Databricks (Spark, notebooks, Delta Lake) to design, build, and scale data workflows end-to-end.
• Deep understanding of cloud data environments (Azure or AWS) and modern data pipeline orchestration (Delta Live Tables, workflow automation).

Data Engineering & Quality Management

• Advanced proficiency in SQL and PySpark for large-scale data transformation, integration, and quality control.
• Proven experience designing robust inconsistency detection frameworks (validation layers, anomaly detection, quality metrics).
• Capability to develop and implement automated correction algorithms, from business rule definition to deployment in production.
• Solid knowledge of data quality governance, including testing, monitoring, and continuous improvement.

Data Science & Analytical Insight

• Strong skills in Python (pandas, scikit-learn, PySpark MLlib) for advanced analysis, pattern discovery, and model development.
• Ability to design analytical approaches to uncover hidden patterns, detect anomalies, and explain data discrepancies.
• Proven experience in timeseries management and statistics.
• Track record of translating complex business challenges into actionable data models and measurable outcomes.

Industrialization & Delivery

• Experience deploying, scaling, and maintaining data science solutions in production environments.
• Familiarity with DevOps/MLOps practices (CI/CD, version control, testing, monitoring) to ensure reliability and reproducibility.
• Strong focus on documentation, traceability, and maintainability of solutions over time.
• Demonstrated expertise in managing Git repositories, including branching strategies, code reviews, and collaborative workflows, as well as maintaining comprehensive and up-to-date project documentation within Git platforms.

Soft skills

Leadership, Initiative & Collaboration

• Proven ability to take initiative: propose new analytical approaches, identify opportunities for data quality improvement, and challenge existing processes.
• Comfortable collaborating with business and technical stakeholders, turning complex data insights into strategic recommendations.
• Capable of leading operational adoption of solutions, supporting users, and driving continuous enhancement of the data ecosystem.

Education and professional background

• Engineering degree or business school, master
• 5 years' experience in similar role is required

Languages

• English (Must) / French (is a plus) / Dutch (is a plus)

If you meet these requirements, then you are the talent we are looking for.

Research shows that men already apply for a position when they meet around 60% of the requirements set by a prospective employer, while women tend to apply only when they feel they are a 100% match. If you do not meet all the requirements but are interested in this role, please let us know.