Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead the development of predictive workforce models for the UK's energy sector.
- Company: Join UK Power Networks and shape the future of energy.
- Benefits: Competitive salary, bonus, 25 days leave, private medical cover, and more.
- Why this job: Make a strategic impact on sustainability and operational resilience in energy.
- Qualifications: Degree in Maths, Economics, Data Science, or related field; experience in analytics.
- Other info: Collaborative environment with opportunities to influence key business decisions.
The predicted salary is between 36000 - 60000 £ per year.
Are you ready to make a strategic impact and help shape the future of the UK's energy sector? At UK Power Networks, we are searching for a talented Data Scientist to lead the development of predictive workforce models that will support our operational needs, regulatory commitments, and ambitious Net Zero goals for the upcoming price control period. Join us at our Human Resources team in London and contribute to ensuring our business stays ahead in meeting both customer expectations and Ofgem requirements.
You will have the opportunity to take ownership of forecasting workforce demand, analyse large datasets for trends and actionable insights, and present your findings in ways that inform and influence key business decisions. Your expertise in Python, statistical methods, causal modelling (such as Chain Modelling), and data visualisation will be integral as you collaborate with HR, business leaders, and cross‑functional teams to deliver robust, future‑focused workforce planning.
Imagine your insights not only shaping long‑term strategy but also helping secure the operational resilience and sustainability of the UK's energy infrastructure. If you have hands‑on experience with Databricks, GitHub, and a background in data‑driven modelling within a corporate environment, all the better.
We're seeking someone with a degree in Maths, Economics, Data Science, Statistics, Computer Science or a related field, with proven experience in analytics and workforce modelling. In return, we offer a competitive salary dependent on your experience, a 7.5% bonus, and a generous benefits package including:
- 25 days annual leave plus bank holidays
- Private medical cover
- Enhanced reservist leave
- An excellent pension scheme
- Tenancy loan deposit
- Season ticket loan
- Tax‑efficient benefits for cycling, home technology and green car leasing
- Occupational health support
- Retail discounts
- Discounted gym membership
- Access to our Employee Assistance Programme
Applications close on 25/01/2026. If you are passionate about data science and eager to play a key role in the UK's energy transition, apply now and help us build a smarter, greener future.
Data Scientist - Workforce Modelling in City of London employer: UK Power Networks (Operations) Ltd
Contact Detail:
UK Power Networks (Operations) Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Workforce Modelling in City of London
✨Tip Number 1
Network like a pro! Reach out to current employees at UK Power Networks on LinkedIn. Ask them about their experiences and any tips they might have for your application. Personal connections can give you an edge!
✨Tip Number 2
Prepare for the interview by brushing up on your Python skills and data visualisation techniques. Be ready to discuss how you've used these in past projects, especially in workforce modelling. Show them you’re the perfect fit!
✨Tip Number 3
Don’t just focus on your technical skills; highlight your ability to collaborate with cross-functional teams. Share examples of how your insights have influenced business decisions. They want to see you as a team player!
✨Tip Number 4
Finally, apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining us at UK Power Networks. Let’s make a difference together!
We think you need these skills to ace Data Scientist - Workforce Modelling in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the job description. Highlight your experience with Python, statistical methods, and workforce modelling. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for data science and how you can contribute to our Net Zero goals. Let us know why you're excited about shaping the future of the UK's energy sector.
Showcase Your Projects: If you've worked on relevant projects, don’t hold back! Include examples of your work with Databricks, GitHub, or any data-driven modelling. We love seeing real-world applications of your skills.
Apply Through Our Website: Remember, the best way to apply is through our website. It’s straightforward and ensures your application gets to the right place. We can’t wait to see what you bring to the table!
How to prepare for a job interview at UK Power Networks (Operations) Ltd
✨Know Your Data Science Stuff
Make sure you brush up on your Python skills and statistical methods before the interview. Be ready to discuss your experience with causal modelling and data visualisation, as these are key for the role. Prepare examples of how you've used these skills in past projects.
✨Understand the Company’s Goals
Familiarise yourself with UK Power Networks' mission, especially their Net Zero goals. Show that you understand how your role as a Data Scientist can contribute to their strategic objectives. This will demonstrate your genuine interest in the company and its future.
✨Prepare for Scenario Questions
Expect questions that ask you to solve hypothetical problems related to workforce modelling. Think about how you would approach forecasting workforce demand or analysing large datasets. Practising these scenarios can help you articulate your thought process clearly during the interview.
✨Showcase Your Collaboration Skills
Since you'll be working with HR and cross-functional teams, be prepared to discuss your teamwork experiences. Share specific examples of how you've collaborated with others to achieve a common goal, particularly in a corporate environment. This will highlight your ability to work effectively within a team.
