Data Scientist – Energy Systems Validation (Energy Sector Experience Required)
Data Scientist – Energy Systems Validation (Energy Sector Experience Required)

Data Scientist – Energy Systems Validation (Energy Sector Experience Required)

Stafford Full-Time 36000 - 60000 £ / year (est.) Home office (partial)
G

At a Glance

  • Tasks: Validate AI/ML models for energy systems and grid automation through rigorous testing and analysis.
  • Company: GE Vernova is leading the charge towards sustainable energy solutions and innovative grid technologies.
  • Benefits: Enjoy flexible work agreements, competitive benefits, and opportunities for personal development.
  • Why this job: Join a dynamic team making a real impact in the energy transition with cutting-edge projects.
  • Qualifications: PhD, Master’s, or Bachelor’s in Data Science or related field, with experience in model validation and energy systems.
  • Other info: Collaborate with experts in a supportive environment focused on innovation and excellence.

The predicted salary is between 36000 - 60000 £ per year.

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.

The ideal candidate will have significant experience in the energy sector, specifically in energy systems and grid automation, or in related domains such as smart infrastructure (e.g., connected buildings, utilities) or industrial automation (e.g., SCADA, PLC systems, Industry 4.0). They should have a strong understanding of how to apply data science and data engineering techniques to develop, validate, and enhance AI/ML models within these complex and data-rich environments.

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.

Must-Have Requirements:

  • 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.
  • Significant experience working in the energy sector, particularly in energy systems, grid automation, or smart grid technologies.
  • Solid experience in validating AI/ML models, ensuring they meet business and technical requirements.
  • Strong 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.

Nice-to-Have Requirements:

  • 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.
  • 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 GE Grid Solutions plays a pivotal role in integrating Renewables onto the grid to drive to carbon neutral. In Grid Solutions we help enable the transition for a greener more reliable Grid. GE 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 bring a solution-focused, positive approach to each one to do your best. Surrounded by committed, loyal colleagues, if you can dare to bring your ingenuity and desire to make an impact, you’ll be exposed to game-changing, diverse projects that truly allow you to play your part in the energy transition.

A key role in a dynamic, international working environment with a large degree of flexibility of work agreements. Competitive benefits, and great development opportunities - including private health insurance.

Data Scientist – Energy Systems Validation (Energy Sector Experience Required) employer: GE Vernova's Grid Software

At GE Vernova, we are committed to fostering a collaborative and innovative work culture that empowers our employees to make a meaningful impact in the energy sector. As a Data Scientist focusing on AI/ML model validation, you will be part of a dynamic team dedicated to advancing grid technologies, with access to competitive benefits and exceptional growth opportunities in a flexible international environment. Join us to electrify and decarbonise the world while working on cutting-edge projects that shape the future of energy.
G

Contact Detail:

GE Vernova's Grid Software Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Data Scientist – Energy Systems Validation (Energy Sector Experience Required)

Tip Number 1

Familiarise yourself with the latest trends in energy systems and grid automation. Understanding current technologies and innovations will not only help you during interviews but also demonstrate your genuine interest in the field.

Tip Number 2

Network with professionals in the energy sector, especially those involved in AI/ML applications. Attend industry conferences or webinars to connect with potential colleagues and learn about their experiences, which can provide valuable insights for your application.

Tip Number 3

Showcase your hands-on experience with AI/ML model validation by discussing relevant projects or case studies during networking events. This practical knowledge can set you apart from other candidates and highlight your capability to contribute effectively.

Tip Number 4

Prepare to discuss specific statistical techniques and validation methodologies you have used in past roles. Being able to articulate your approach to model performance metrics will demonstrate your expertise and readiness for the challenges of this position.

We think you need these skills to ace Data Scientist – Energy Systems Validation (Energy Sector Experience Required)

AI/ML Model Validation
Statistical Techniques
Model Performance Metrics
Data Wrangling
Feature Engineering
Python Programming
R Programming
MATLAB Proficiency
Machine Learning Frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
Cloud Platforms (e.g., AWS, Azure, GCP)
Data Visualization Tools (e.g., Tableau, Power BI)
Automated Testing Strategies
Data Governance Policies
Collaboration with Data Engineers and ML Engineers
Communication Skills

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights your experience in the energy sector, particularly in energy systems and grid automation. Use specific examples of projects or roles that demonstrate your skills in validating AI/ML models.

Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss how your background aligns with the responsibilities outlined in the job description, especially your experience with AI/ML model validation and data analysis.

Showcase Relevant Skills: Clearly list your technical skills relevant to the position, such as proficiency in programming languages like Python or R, and familiarity with machine learning frameworks. Highlight any experience you have with cloud platforms and data visualization tools.

Prepare for Technical Questions: Anticipate technical questions related to model validation and data science methodologies. Be ready to discuss your approach to testing and validating AI/ML models, as well as how you handle discrepancies in model performance.

How to prepare for a job interview at GE Vernova's Grid Software

Showcase Your Energy Sector Experience

Make sure to highlight your previous experience in the energy sector during the interview. Discuss specific projects or roles where you validated AI/ML models or worked with grid automation, as this will demonstrate your relevance to the position.

Prepare for Technical Questions

Expect technical questions related to data science and model validation methodologies. Brush up on statistical techniques, performance metrics, and programming languages like Python or R, as these are crucial for the role.

Demonstrate Problem-Solving Skills

Be ready to discuss how you've identified and addressed discrepancies in model performance in past projects. Use examples to illustrate your analytical thinking and problem-solving abilities, which are key for this role.

Communicate Clearly and Effectively

Since you'll need to present validation results to stakeholders, practice explaining complex concepts in simple terms. This will show your ability to communicate effectively with both technical and non-technical audiences.

Data Scientist – Energy Systems Validation (Energy Sector Experience Required)
GE Vernova's Grid Software
G
  • Data Scientist – Energy Systems Validation (Energy Sector Experience Required)

    Stafford
    Full-Time
    36000 - 60000 £ / year (est.)

    Application deadline: 2027-07-06

  • G

    GE Vernova's Grid Software

Similar positions in other companies
UK’s top job board for Gen Z
discover-jobs-cta
Discover now
>