Senior Energy Data & Modelling Analyst

Adecco Portugal

North Warwickshire

Hybrid

GBP 83,000 - 120,000

Full time

2 days ago
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Job summary

Adecco Portugal is seeking a Senior Energy Data & Modelling Analyst for a 6-month contract in Warwick. The role is hybrid, with responsibilities centred on whole-energy-system modelling and data management to inform planning initiatives.

The ideal candidate will have strong experience with energy-system data, DNOs/LAEP, and forecasting, bridging data and modelling across stakeholder groups. Market-rate scope applies for inside IR35 via umbrella.

Qualifications

  • Strong experience with energy-system data and modelling environments.
  • Understanding how datasets underpin modelling activities and decision making.
  • Experience with DNOs, LAEP, and whole-energy-system modelling or forecasting.

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.

Skills

Energy data analysis
Energy modelling
Datasets management
Stakeholder engagement

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

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