National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

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

GE Vernova
Stafford
2 weeks ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist - Graduate

Data Scientist, Math Modelling, Physics

Job Description Summary
Join us in our journey to redefine what's possible with AI and make a lasting impact on the world of Energy.
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 dynamic, forward-thinking, and results-driven Data Scientist who will primarily focus on deriving advanced models for grid innovation applications. 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 to drive efficiency and innovation. The ideal candidate should have significant experience in the energy sector, specifically in grid automation and energy systems.

This role will be responsible for designing and building a common framework for data storage, analytics, and AI model deployment. The Data Scientist will work across different functions within Grid Automation (GA) to identify opportunities for leveraging data and AI to solve critical customer problems, improve efficiencies, and develop scalable solutions. This role will also involve developing Proof of Concepts (POCs) and ensuring the deployment of models on edge or cloud-based systems.

Job Description

Essential Responsibilities:

  • Develop and maintain database structures, schemas, and data models to support AI and machine learning applications.
  • Utilize efficient storage technologies (Relational, Data Lakes, NoSQL, etc.) to manage data storage, access, and security.
  • Design and implement scalable and reliable data pipelines for cleaning, transforming, and extracting features from both structured and unstructured data.
  • Build and maintain integrations with internal and external data sources and APIs.
  • Identify and integrate new datasets that enhance product capabilities and provide actionable insights.
  • Automate the integration of data from various sources into a unified format, tailored to specific business needs.
  • Monitor, optimize, and ensure the scalability of data pipelines.
  • Collaborate with Data Scientists, ML Engineers, and other cross-functional teams to meet data needs for AI/ML models and analytics.
  • Develop and deliver innovative solutions in collaboration with teams across the organization, helping the business leverage AI and data analytics to solve customer challenges.


Must-Have Requirements:

  • PhD, Master's, or Bachelor's degree in Computer Science, Electrical Engineering, or a related field with hands-on experience in data engineering.
  • Significant experience in the energy sector, specifically in grid automation or energy systems, with expertise in working with energy-related data.
  • Significant experience in data engineering, specifically in creating and managing data pipelines for structured and unstructured data.
  • Solid experience with database management systems (e.g., relational databases like PostgreSQL, NoSQL databases like Cassandra and MongoDB).
  • Solid expertise in utilizing data storage technologies such as Data Lakes, NoSQL, and relational databases.
  • Solid experience in building scalable and reliable data pipelines for data transformation and feature extraction.
  • Solid proficiency in scientific programming languages like Python, Scala, Java, or SQL.
  • Solid experience with cloud platforms (AWS, GCP, Azure) and cloud services for data storage, processing, and analytics.


Nice-to-Have Requirements:

  • Familiarity with big data technologies such as Hadoop, Kafka, and similar tools.
  • Familiarity with version control systems like Git.
  • Experience with GraphDB, MongoDB, SQL/NoSQL, MS Access, and other databases.
  • Ability to work in a collaborative, multi-functional environment, demonstrating a proactive approach and solid communication skills.
  • Familiarity with data warehousing principles and technologies.


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.

AboutGEVGrid Solutions:

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 full fill the needs of tomorrow. With a focus on growth and sustainability GE Grid Solutions plays a pivotable 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.

Why we come to work:

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.

What we offer:

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.

Additional Information

Relocation Assistance Provided:No

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Get a Better Data Science Job After a Lay-Off or Redundancy

Redundancy can be tough to face, especially in a competitive field like data science. But it’s important to know: your experience, analytical thinking, and modelling skills are still in demand. Across sectors like healthcare, finance, e-commerce, government and AI startups, UK employers continue to seek data scientists who can deliver value through insight, prediction, and automation. This guide will walk you through how to bounce back from redundancy with purpose and clarity—whether you're a data analyst looking to step up, a mid-level data scientist, or a machine learning specialist seeking a better-aligned opportunity.

Data Science Jobs Salary Calculator 2025: Find Out What You Should Earn in the UK

Why last year’s pay survey is already out of date for UK data scientists “Am I being paid enough?” Every data professional eventually asks that question—often after a teammate reveals a hefty counter‑offer, a recruiter shares a six‑figure opening, or a headline trumpets the latest multimillion‑pound AI investment. Yet salary guides published even twelve months ago belong in a museum. Generative‑AI hype re‑priced Machine‑Learning Engineer roles, LLM fine‑tuning turned Prompt Engineering into a genuine career path, & fresh regulation forced companies to hire Responsible‑AI Officers on senior‑scientist money. To cut through the noise, DataScience‑Jobs.co.uk distilled a transparent, three‑factor formula. Insert your role, your region, & your seniority, and you’ll get a realistic 2025 salary benchmark—no stale averages, no vague ranges. This article walks you through the formula, examines the forces pushing data‑science pay ever higher, and offers five concrete actions to boost your market value within ninety days.

How to Present Data Science Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

The ability to communicate clearly is now just as important as knowing how to build a predictive model or fine-tune a neural network. In fact, many UK data science job interviews are now designed to test your ability to explain your work to non-technical audiences—not just your technical competence. Whether you’re applying for your first data science role or moving into a lead or consultancy position, this guide will show you how to structure your presentation, simplify technical content, design effective visuals, and confidently answer stakeholder questions.