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- Tasks: Develop predictive workforce models and analyse data to forecast operational needs.
- Company: Join UK Power Networks, a leader in energy transition and sustainability.
- Benefits: Enjoy 25 days annual leave, private medical cover, and tax-efficient benefits.
- Why this job: Make a strategic impact on the UK's energy infrastructure and Net Zero goals.
- Qualifications: Degree in relevant field and strong skills in Python and data analysis.
- Other info: Collaborative environment with excellent career growth and development opportunities.
The predicted salary is between 36000 - 60000 £ per year.
This Data Scientist - Workforce Modelling will report to the Analytics and Dev Ops Lead and will work within Human Resources based in our London, Elephant and Castle office. You will be a permanent employee. UK Power Networks is looking for a talented Data Scientist to join our team and lead the development of predictive workforce models. This is a unique opportunity to make a strategic impact by helping us forecast workforce demand for the next price control period (2028-2032). Your work will ensure we have the right resources in place to meet operational needs, regulatory obligations, and our Net Zero commitments.
Accurate workforce forecasting is critical to:
- Supporting the UK's energy transition and Net Zero goals.
- Meeting Ofgem regulatory requirements and price control targets.
- Maintaining operational resilience and delivering exceptional customer service.
Your insights will shape long-term workforce strategy and influence the future of the UK's energy infrastructure.
What You’ll Do
- Develop and maintain predictive workforce models for 2028-2032.
- Analyse large datasets to identify trends, patterns, and actionable insights.
- Apply causal modelling techniques (e.g., Chain Modelling) to understand workforce drivers.
- Collaborate with HR, business leaders, and cross-functional teams.
- Present findings through clear reports, dashboards, and presentations.
Essential Skills
- Strong proficiency in Python for data analysis and modelling.
- Expertise in causal modelling techniques, such as Chain Modelling for workforce planning.
- Solid understanding of statistical methods and workforce modelling principles.
- Experience working with large datasets and data visualization tools.
- Excellent communication and stakeholder engagement skills.
Preferred Experience
- Hands-on experience with Databricks for big data processing and analytics.
- Familiarity with GitHub for version control and collaborative development.
- Background in workforce or operations modelling within a corporate environment.
Qualifications
- Degree in Maths, Economics, Data Science, Statistics, Computer Science, or a related field.
- Proven experience in data-driven modelling and analytics.
You will attract a salary dependent on experience and a bonus of 7.5%. Close Date: 25/01/2026.
Benefits
- 25 Days Annual Leave plus bank holidays.
- Private Medical Cover / Simply Health.
- Reservist Leave – Additional 18 days full pay and 22 unpaid.
- Personal Pension Plan – Personal contribution rates of 4% or 5% (UK Power Networks will make a corresponding contribution of 8% or 10%).
- Tenancy Loan Deposit Scheme, Season Ticket Loan.
- Tax‑efficient benefits: Cycle to Work, Home & Tech, and Green Car Leasing Schemes.
- Occupational Health support.
- Switched On – a scheme providing discount on hundreds of retailers' products.
- Discounted gym membership.
- Employee Assistance Programme.
Data Scientist - Workforce Modelling employer: UK Power Networks
Contact Detail:
UK Power Networks Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Workforce Modelling
✨Tip Number 1
Network like a pro! Reach out to current employees at UK Power Networks on LinkedIn. A friendly chat can give you insider info and might just get your foot in the door.
✨Tip Number 2
Show off your skills! Prepare a mini-project or case study that showcases your expertise in predictive modelling and data analysis. Bring it up during interviews to stand out from the crowd.
✨Tip Number 3
Practice makes perfect! Get comfortable with common interview questions for data scientists, especially those related to causal modelling and workforce planning. We can help you with mock interviews if you need.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, you’ll be one step closer to joining a team that’s making a real impact in the energy sector.
We think you need these skills to ace Data Scientist - Workforce Modelling
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist role. Highlight your experience with Python, causal modelling techniques, and any relevant projects you've worked on. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about workforce modelling and how you can contribute to our Net Zero goals. Keep it concise but impactful – we love a good story!
Showcase Your Data Skills: When applying, don’t forget to mention your experience with large datasets and data visualisation tools. If you've used Databricks or GitHub, give us the details! We’re keen to see your technical prowess in action.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status. Let’s get you on board!
How to prepare for a job interview at UK Power Networks
✨Know Your Data Inside Out
Before the interview, dive deep into your past projects involving data analysis and workforce modelling. Be ready to discuss specific datasets you've worked with, the techniques you applied, and the insights you derived. This will show your expertise and how you can contribute to developing predictive workforce models.
✨Master Causal Modelling Techniques
Since causal modelling is a key part of the role, brush up on techniques like Chain Modelling. Prepare to explain how you've used these methods in previous roles to understand workforce drivers. Being able to articulate your thought process will impress the interviewers.
✨Showcase Your Communication Skills
As you'll be collaborating with HR and business leaders, it's crucial to demonstrate your ability to present complex data clearly. Bring examples of reports or dashboards you've created and be prepared to discuss how you tailored your findings for different stakeholders.
✨Familiarise Yourself with Tools
If you have experience with Databricks or GitHub, make sure to highlight it during the interview. If not, do a bit of research on these tools and be ready to discuss how you would use them in the context of workforce modelling. Showing that you're proactive about learning new technologies can set you apart.
