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Data scientist – energy systems validation (energy sector experience required)

Stafford
GE Vernova
Data scientist
Posted: 8h ago
Offer description

Job Description Summary
GE Vernova is accelerating the path to more reliable, affordable, and sustainable energy, helping our customers power economies and deliver vital electricity for health, safety, and security. Are you excited about the opportunity to electrify and decarbonize the world?

We are seeking a highly skilled and results-driven Data Scientist - Validation to join our team, focusing on validating AI/ML models for grid innovation applications. This role involves 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 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, or related domains such as smart infrastructure or industrial automation. They should have a strong understanding of applying data science and engineering techniques to develop, validate, and improve AI/ML models in complex, data-rich environments.

Essential Responsibilities:
* Design and conduct experiments to test and validate AI/ML models in energy systems and grid automation.
* Establish validation frameworks to ensure models meet performance standards and business objectives.
* Develop test procedures to validate models with real and simulated grid data.
* Analyze model performance against real-world data for accuracy, reliability, and scalability.
* Identify discrepancies between expected and actual model behavior, providing insights for improvement.
* Implement automated testing strategies and pipelines to streamline validation processes.
* Collaborate with Data and ML Engineers to enhance data quality and model deployment.
* Ensure validation processes adhere to data governance policies and standards.
* Communicate validation results and insights clearly to stakeholders.
Must-Have Requirements:
* Degree in Data Science, Computer Science, Electrical Engineering, or related field with experience in model validation.
* Experience in the energy sector, especially in energy systems or grid automation.
* Proven experience validating AI/ML models to meet requirements.
* Strong knowledge of statistical techniques and validation methodologies.
* Proficiency in Python, R, or MATLAB.
* Experience with data wrangling, feature engineering, and dataset preparation.
* Knowledge of machine learning frameworks like TensorFlow, PyTorch, Scikit-learn.
* Experience with cloud platforms (AWS, Azure, GCP) and deploying models.
* Ability to use data visualization tools like Tableau or Power BI.
Nice-to-Have:
* Familiarity with big data tools like Hadoop, Kafka, Spark.
* Knowledge of data governance and validation standards in energy.
* Experience with distributed computing and large-scale deployment.
* Strong communication skills for explaining complex validation results.
At GE Vernova - Grid Automation, you'll work on innovative projects shaping the future of energy, in a collaborative environment that values your expertise.

About GEV Grid Solutions:
We are leaders in advanced grid technologies, accelerating the transition to a more energy-efficient and renewable-powered grid. Our focus is on growth and sustainability, helping to integrate renewables and achieve a carbon-neutral future.

Why work with us:
Our engineers face unique challenges, with projects that allow you to bring ingenuity and make an impact. Join a team of committed colleagues working on diverse, game-changing projects in the energy transition.

What we offer:
A dynamic, international environment with flexible work arrangements, competitive benefits, and development opportunities, including private health insurance.

Additional Information:
Relocation Assistance Provided: No #J-18808-Ljbffr

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