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- Tasks: Drive innovative solutions for electricity networks using data science and engineering.
- Company: Join a forward-thinking energy company focused on resilience and performance.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Why this job: Make a real impact in the energy sector by transforming technology into practical solutions.
- Qualifications: Experience in data science, AI/ML, and strong Python programming skills required.
- Other info: Collaborative environment with exciting projects and career advancement opportunities.
The predicted salary is between 30000 - 50000 £ per year.
Data Scientist (Energy) drives the development and delivery of cutting-edge solutions that strengthen the performance and resilience of electricity networks. Operating at the intersection of engineering, data science, and applied research, the role focuses on identifying operational challenges in the energy sector and transforming emerging technologies into practical, real-world applications.
This position works collaboratively with Distribution Network Operators (DNOs), universities, research partners, and internal teams to explore innovation opportunities and co-develop impactful solutions. The engineer contributes technical expertise to data-driven initiatives, shaping models, algorithms, and analytical approaches that support decision-making and innovation outcomes. They play a hands-on role throughout the lifecycle of innovation projects, from early idea generation and feasibility assessment through to prototyping, testing, and deployment.
Strong communication and collaboration skills are essential, as the role interfaces with engineering, product, consulting, and business stakeholders to design and refine technical solutions that meet sector needs. The ideal candidate brings deep knowledge of energy systems, experience with AI/ML technologies, and strong programming capabilities.
Qualifications & Experience:- Experience within the energy sector, ideally focused on electricity networks or smart grids
- Experience applying AI/ML technologies in engineering or operational settings
- Strong Python programming skills and familiarity with data analysis, machine learning, or simulation frameworks
- Ability to collaborate effectively in multidisciplinary teams and explain complex technical concepts to diverse audiences
- Work closely with DNOs to understand operational challenges, explore innovation opportunities, and co-develop solutions that enhance network performance and resilience.
- Partner with universities and research institutions to translate emerging technologies and scientific advancements into practical, real-world applications.
- Contribute technical expertise to data-driven projects, helping shape models, algorithms, and analytical approaches that drive innovation outcomes.
- Communicate effectively with engineering, product, consulting, and business teams to design, refine, and deliver technical solutions.
- Support the full lifecycle of innovation projects, from idea generation and feasibility analysis to prototyping, testing, and deployment.
In this role, you will work at the intersection of data science, engineering, and applied research to design and deliver innovative solutions for electricity networks. You’ll collaborate closely with Distribution Network Operators, research institutions, and internal teams to understand operational challenges and turn emerging technologies into practical, deployable solutions that drive resilience and performance.
You’ll contribute across the full innovation lifecycle, from early concept development and feasibility assessment through to prototyping, testing, and deployment. Supported by a collaborative environment, you’ll be encouraged to take ownership of your ideas, apply creative problem-solving, and help shape data-driven approaches that influence real-world decision-making.
Key responsibilities include:- Collaborate & Discover – Work with DNOs to understand operational challenges and identify innovation opportunities
- Design & Deliver – Develop data-driven models, algorithms, and analytical approaches that support network optimisation
- Innovate & Translate – Partner with universities and research bodies to turn emerging technologies into applied solutions
- Communicate & Influence – Engage with engineering, product, consulting, and business teams to refine technical outcomes
- Prototype & Deploy – Support innovation projects from ideation through testing and real-world implementation
To succeed, you will bring strong experience in data science or AI applied within the energy sector, combined with the ability to collaborate across disciplines and communicate complex ideas clearly. You’ll be comfortable applying advanced analytics in operational environments and motivated to turn insight into action.
You should have:
- Experience working within the energy sector, ideally electricity networks or smart grids
- Experience applying AI/ML techniques in engineering or operational contexts
- Strong Python programming skills and experience with data analysis or machine learning frameworks
- Proven ability to collaborate within multidisciplinary teams and engage diverse stakeholders
- Data Engineering
- Data Modeling
- Python
Data Scientist employer: CGI
Contact Detail:
CGI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Network like a pro! Attend industry events, webinars, and meetups related to energy and data science. This is your chance to connect with potential employers and showcase your passion for the field.
✨Tip Number 2
Don’t underestimate the power of LinkedIn! Make sure your profile is up-to-date and reflects your skills in Python, AI/ML, and energy systems. Engage with posts, share your insights, and reach out to people in the industry.
✨Tip Number 3
Prepare for interviews by practising common data science questions and case studies. Be ready to discuss how you’ve tackled operational challenges in the energy sector and how your solutions made an impact.
✨Tip Number 4
Apply through our website! We’re always on the lookout for talented individuals who can drive innovation in the energy sector. Your next big opportunity could be just a click away!
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the Data Scientist role. Highlight your experience in the energy sector, especially with electricity networks and AI/ML technologies. We want to see how your skills align with what we’re looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about the energy sector and how your background makes you a perfect fit for our team. Don’t forget to mention any collaborative projects you've worked on!
Showcase Your Technical Skills: We love seeing strong programming skills, especially in Python! Include specific examples of projects where you’ve applied data analysis or machine learning techniques. This will help us understand your hands-on experience.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It’s the best way for us to receive your application and ensure it gets the attention it deserves. We can’t wait to see what you bring to the table!
How to prepare for a job interview at CGI
✨Know Your Energy Sector
Make sure you brush up on your knowledge of electricity networks and smart grids. Understand the current challenges in the energy sector and be ready to discuss how your skills can help address these issues. This will show your genuine interest and expertise in the field.
✨Showcase Your AI/ML Experience
Prepare specific examples of how you've applied AI and machine learning technologies in previous roles. Be ready to explain the impact of your work, especially in operational settings. This will demonstrate your practical experience and problem-solving abilities.
✨Demonstrate Collaboration Skills
Since this role involves working with various stakeholders, think of instances where you've successfully collaborated with multidisciplinary teams. Highlight your communication skills and how you’ve translated complex technical concepts for diverse audiences.
✨Be Ready to Discuss Python Projects
As strong Python programming skills are essential, come prepared to talk about your past projects involving data analysis or machine learning frameworks. If possible, share code snippets or project outcomes that illustrate your capabilities and contributions.
