Data Scientist - Workforce Modelling
| Posting date: | 12 January 2026 |
|---|---|
| Hours: | Full time |
| Closing date: | 26 January 2026 |
| Location: | London, London, SE1 6NP |
| Remote working: | Hybrid - work remotely up to 2 days per week |
| Company: | UK Power Networks |
| Job type: | Permanent |
| Job reference: | 81966_1768207291 |
Summary
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 (2028-2032). 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, and 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.