Senior Energy Data & Modelling Analyst

Adecco Portugal; Warwick; Hybrid; GBP 60,000 - 90,000; Full time

Job summary

Senior Energy Data & Modelling Analyst in Warwick is a 6-month contract with hybrid working. The role supports whole-energy-system modelling and planning initiatives, bridging data sourcing and modelling outcomes across national, regional and local datasets.

Ideal candidates will have strong energy-system data expertise, familiarity with DNOs, LAEP, and forecasting, with experience in energy network modelling and scenario planning.

Qualifications

• Strong experience with energy-system data and modelling environments.
• Understanding how energy datasets underpin modelling activities and decision making.
• Knowledge of energy network data, forecasting, scenario planning or system modelling.

Responsibilities

• Analyse, interpret and manage complex energy-system datasets.
• Ensure datasets are structured and aligned for modelling activities.
• Support development and enhancement of whole-energy-system models.
• Understand and reconcile national, regional and local energy datasets.
• Translate modelling requirements into data requirements and vice versa.
• Work with stakeholders across modelling, planning and analysis functions.
• Contribute to scenario modelling, forecasting and energy planning projects.
• Provide insight into modelling assumptions, inputs and outputs.

Skills

Energy data

Modelling environments

LAEP

DNOs experience

Forecasting

Scenario modelling

Tools

Python

Job description

Senior Energy Data & Modelling Analyst

6-Month Contract (Initial) Warwick/Hybrid - Market Rates (Inside IR35 via umbrella)

We're supporting a leading energy organisation seeking an experienced Senior Energy Data & Modelling Analyst to join a specialist team working on whole energy system modelling and planning initiatives.

This role sits at the intersection of energy-system modelling and energy data, requiring someone who understands not only how energy datasets are sourced, structured and managed, but also how they feed into and influence modelling outcomes.

This is an excellent opportunity for an individual with experience across DNOs, Local Area Energy Planning (LAEP), energy network modelling, forecasting or whole-energy-system analysis.

Key Responsibilities

• Analyse, interpret and manage complex energy-system datasets.
• Ensure datasets are appropriately structured and aligned for modelling activities.
• Support the development and enhancement of whole-energy-system models.
• Understand and reconcile national, regional and local energy datasets.
• Translate modelling requirements into data requirements and vice versa.
• Work with stakeholders across modelling, planning and analysis functions.
• Contribute to scenario modelling, forecasting and energy planning projects.
• Provide insight into modelling assumptions, inputs and outputs.

Essential Experience

• Strong experience working with energy-system data and modelling environments.
• Understanding of how energy datasets underpin modelling activities and decision making.
• Knowledge of energy network data, forecasting, scenario planning or system modelling.
• Experience within one or more of the following:
  • Distribution Network Operators (DNOs)
  • Energy consultancies
  • Energy network modelling organisations
  • Local Area Energy Planning (LAEP)
  • Whole Energy Systems modelling
  • Energy forecasting and scenario modelling
• Experience working with multiple energy vectors, such as:
  • Electricity
  • Gas
  • Storage
  • Biomethane
  • Broader whole-energy-system datasets

Desirable Experience

• Local Area Energy Planning (LAEP).
• Understanding of DNO datasets and network planning processes.
• Python or other relevant analytical/programming experience.
• Experience reconciling local and national energy datasets.
• Knowledge of Future Energy Scenarios (FES) or net-zero modelling programmes.

If you have a strong understanding of how energy datasets feed into modelling and can bridge the gap between data and whole-energy-system analysis, we'd love to hear from you.