Data Scientist - Workforce Modelling

Data Scientist - Workforce Modelling

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.

You will attract a salary dependant on experience and a bonus of 7.5%

Please note we are looking to schedule interview for W/C 26th January 

Close Date: 22/01/2026.

We also provide the following additional 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 – scheme providing discount on hundreds of retailers' products
Discounted gym membership
Employee Assistance Programme

About the Role

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.

Why This Role Matters

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.

What We're Looking For

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.

Ready to Shape the Future?

If you're passionate about data science and want to play a key role in the UK's energy transition, apply now and help us build a smarter, greener future.

Health & Safety Responsibilities:

Managers and supervisors carry both legal and company responsibilities for ensuring the health and safety of their employees, those under their control and those who might be affected by the work undertaken, i.e. public, visitors and employees of other organisations. This includes briefing individuals working for them and ensuring there is the necessary understanding, competence and application of requirements to work safely and without harming the environment.

Employees will ensure they understand the health and safety risks involved in their work activities and their responsibility to apply the controls needed to manage those risks to acceptable levels. Similarly where work activities can have an adverse impact upon the environment, and where there are legal requirements, employees will understand those impacts and the controls they must ensure are applied.

If in doubt ask!

We are committed to equal employment opportunity regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity workplace.