GE Vernova

Lead AI Model Validation Scientist – Energy Systems

LocationMarkham, ON
Job TypeFull-time

About This Job


Job Description Summary

GE Vernova is accelerating the path to more reliable, affordable, and sustainable energy, while helping our customers power economies and deliver the electricity that is vital to health, safety, security, and improved quality of life. Are you excited at the opportunity to electrify and decarbonize the world?

We are seeking a highly skilled and results-driven Data Scientist Validation to join our team, primarily focusing on validating AI/ML models for grid innovation applications. This role will involve rigorous testing, validation, and verification of AI/ML models with grid data to ensure they meet accuracy, performance, and operational standards within energy systems. Reporting to the AI leader in the CTO organization, the Data Scientist will collaborate closely with Grid Automation (GA) product lines, R&D teams, product management, and other GA functions.

The ideal candidate will have significant experience in the energy sector, specifically in energy systems and grid automation, with a solid understanding of how to apply data science techniques to run and validate and improve AI/ML models in the energy domain.


Job Description


Essential Responsibilities:

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 pipeline 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.


Required Qualifications:

PhD, Master’s, or Bachelor’s degree in Data Science, Computer Science, Electrical Engineering, or a related field with hands-on experience in model validation.
Minimum of 3 years of industry experience.


Desired Qualifications:

Significant experience working in the energy sector, particularly in energy systems, grid automation, or smart grid technologies.
Proven experience in validating AI/ML models, ensuring they meet business and technical requirements.
Excellent knowledge of statistical techniques, model performance metrics, and validation methodologies for AI/ML models.
Proficiency in programming languages such as Python, R, or MATLAB.
Experience with data wrangling, feature engineering, and preparing datasets for model validation.
Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and model evaluation techniques.
Experience with cloud platforms (e.g., AWS, Azure, GCP) and deployment of models in cloud environments.
Experience with data visualization tools such as Tableau, Power BI, or similar to effectively present validation results and insights.
Familiarity with big data tools and technologies, such as Hadoop, Kafka, and Spark.
Familiarity with data governance frameworks and validation standards in the energy sector.
Knowledge of distributed computing environments and model deployment at scale.
Excellent communication skills, with the ability to clearly explain complex validation results to non-technical stakeholders.


Additional Information


Relocation Assistance Provided: No

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