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Data Scientist – Grid Innovation Model Development (Energy Sector Experience Required)

Data Scientist – Grid Innovation Model Development (Energy Sector Experience Required)
AL8238 UK Grid Solutions Limited
Stafford
GBP 40.000 - 60.000
Richiesta urgente
Oggi
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Data Scientist – Grid Innovation Model Development (Energy Sector Experience Required)

Sii tra i primi a mandare la candidatura.
AL8238 UK Grid Solutions Limited
Stafford
GBP 40.000 - 60.000
Sii tra i primi a mandare la candidatura.
Oggi
Descrizione del lavoro

Data Scientist – Grid Innovation Model Development (Energy Sector Experience Required)

Job Description Summary

GE Vernova is accelerating the path to more reliable, affordable, and sustainable energy, helping customers power economies and deliver vital electricity for health, safety, and quality of life. Are you excited about electrifying and decarbonizing the world?

We seek a skilled Data Scientist - Validation to join our team, focusing on validating AI/ML models for grid innovation applications. The role involves testing, validation, and verification of models with grid data to ensure they meet standards. Reporting to the AI leader in the CTO organization, the Data Scientist will collaborate with Grid Automation (GA) product lines, R&D, product management, and other GA functions.

The ideal candidate will have experience in the energy sector, especially in energy systems, grid automation, or related domains like smart infrastructure or industrial automation. They should understand applying data science and engineering techniques to develop and validate AI/ML models in complex, data-rich environments.

Essential Responsibilities
  • Design experiments to test and validate AI/ML models in energy systems and grid automation.
  • Establish validation frameworks to meet performance standards.
  • Develop test procedures with real and simulated grid data.
  • Analyze model performance for accuracy and reliability.
  • Identify discrepancies and provide insights for improvement.
  • Implement automated testing and validation pipelines.
  • Collaborate with Data and ML Engineers to improve data quality and model deployment.
  • Ensure validation processes adhere to data governance and industry standards.
  • Communicate results and insights clearly to stakeholders.
Must-Have Requirements
  • Degree in Data Science, Computer Science, Electrical Engineering, or related with hands-on validation experience.
  • Experience in the energy sector, especially in energy systems or grid automation.
  • Proven experience validating AI/ML models.
  • Knowledge of statistical techniques and validation metrics.
  • Proficiency in Python, R, or MATLAB.
  • Experience with data wrangling, feature engineering, and dataset preparation.
  • Familiarity with frameworks like TensorFlow, PyTorch, or Scikit-learn.
  • Experience with cloud platforms (AWS, Azure, GCP).
  • Data visualization skills (Tableau, Power BI).
Nice-to-Have Requirements
  • Experience with big data tools (Hadoop, Kafka, Spark).
  • Knowledge of data governance and validation standards in energy.
  • Understanding of distributed computing and scaling models.
  • Strong communication skills for explaining complex results.

At GE Vernova - Grid Automation, you'll work on innovative projects shaping the future of energy in a collaborative environment where your expertise is valued.

About GE Grid Solutions: We are advancing grid technologies to enable renewable integration and a greener, reliable energy future. Our goal is to drive the energy transition through innovative products and solutions.

Why work with us: Our engineers face unique challenges in projects that impact the energy landscape. We foster a solution-focused, positive environment with opportunities to make a real impact.

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

Additional Information

Relocation Assistance Provided: No

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* Il benchmark retributivo si basa sugli obiettivi retributivi dei leader del mercato nei rispettivi settori. È pensato per orientare gli utenti Premium nella valutazione delle posizioni aperte e aiutarli a negoziare la propria retribuzione. Tale benchmark non è fornito direttamente dall'azienda, quindi la retribuzione effettiva potrà risultare anche notevolmente superiore o inferiore.

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