Lead Data Scientist

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We are seeking a Lead Data Scientist with solid experience typically gained over a minimum of 5 years in large multinational companies within the energy sector or related industrial domains such as smart infrastructure or industrial automation. The ideal candidate has hands‑on experience in AI/ML model testing, verification, and validation in complex, data‑rich environments.

• Design and conduct experiments to test and validate AI/ML models in the context of energy systems and grid automation applications.
• Establish clear validation frameworks to ensure models meet required performance standards and business objectives.
• Establish test procedures to validate models with real and simulated grid data.
• Analyze model performance against real‑world data to ensure accuracy, reliability, and scalability.
• Identify and address discrepancies between expected and actual model behavior, providing actionable insights to improve model performance.
• Implement automated testing strategies and pipelines to streamline model validation processes.
• Collaborate with Data Engineers and ML Engineers to improve data quality, enhance model performance, and ensure efficient deployment of validated models.
• Ensure that validation processes adhere to data governance policies and industry standards.
• Communicate validation results, insights, and recommendations clearly to stakeholders, including product managers and leadership teams.

• Experience typically gained over +5 years in large multinational companies within the energy sector or related industrial domains such as smart infrastructure or industrial automation.
• Master’s, or Bachelor’s degree in Data Science, Computer Science, Electrical Engineering, or a related field, with hands‑on experience in model validation.
• Solid experience in validating AI/ML models, ensuring they meet business and technical requirements.
• Strong knowledge of statistical techniques, model performance metrics, and AI/ML validation methodologies.
• Proficiency in programming languages such as Python, R, or MATLAB.
• Experience with data wrangling, feature engineering, and dataset preparation for model validation.
• Familiarity with machine learning frameworks (e.g., Tensor Flow, PyTorch, Scikit‑learn) and model evaluation techniques.
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and deploying models in cloud environments.
• Experience with data visualization tools (e.g., Tableau, Power BI) to effectively present validation results and insights.

• Familiarity with big data tools and technologies such as Hadoop, Kafka, and Spark.
• Knowledge of data governance frameworks and validation standards in the energy sector.
• Understanding of distributed computing environments and large‑scale model deployment.
• Strong communication skills, with the ability to clearly explain complex validation results to non‑technical stakeholders.

At GE Vernova - Grid Automation, you will have the opportunity to work on cutting‑edge projects that shape the future of energy. We offer a collaborative environment where your expertise will be valued, and your contributions will make a tangible impact. Join us and be part of a team that is driving innovation and excellence in control systems.

At GEV Grid Solutions we are electrifying the world with advanced grid technologies. As leaders in the energy space our goal is to accelerate the transition for a more energy efficient grid to fulfil the needs of tomorrow. With a focus on growth and sustainability GEV Grid Solutions plays a pivotal role in integrating renewables onto the grid to drive carbon neutrality.

In Grid Solutions we help enable the transition for a greener, more reliable Grid. GEV Grid Solutions has the most advanced and comprehensive product and solutions portfolio within the energy sector.

At GEV, our engineers are always up for the challenge – and we’re always driven to find the best solution. Our projects are unique and interesting, and you’ll need to…