Senior Energy Modeller
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Senior Energy Modeller

Reference: TK - 61
Location
United Kingdom
Salary
Up to £60K
Contract Type
Permanent
Work Arrangement
Remote Working
Skill Requirements
  • Python Engineer

Energy Modeller – ClimateTech Scale-Up (Remote-First | Visa Sponsorship Available)

We’re working with a high-growth ClimateTech scale-up tackling complex, localised energy challenges through deeply technical modelling and optimisation. They partner with public and private sector organisations to design low-carbon energy systems grounded in real-world constraints.

This is a highly technical role suited to someone who enjoys building robust, scalable models and solving optimisation problems that directly influence infrastructure and investment decisions.

The Role
You’ll sit at the core of the modelling team, developing advanced energy models that simulate and optimise systems across generation, storage, and demand. This isn’t high-level analysis — it’s hands-on, algorithm-heavy work where performance, accuracy, and scalability matter.

Key Responsibilities

  • Design and implement advanced energy system models using Python
  • Develop optimisation algorithms to solve complex, multi-variable energy problems
  • Work with large, real-world datasets to model local energy systems (city, regional, asset-level)
  • Build scalable, production-ready modelling tools and pipelines
  • Apply mathematical optimisation techniques (linear, mixed-integer, nonlinear)
  • Translate model outputs into clear recommendations for technical and non-technical stakeholders

Core Requirements

  • Strong Python expertise (this is essential) – including numerical computing and data handling
  • Solid background in algorithms and optimisation techniques
  • Experience with optimisation frameworks (e.g. Pyomo, Gurobi, OR-Tools or similar)
  • Proven experience building and deploying complex models (energy systems or similar domains)
  • Strong mathematical foundation (optimisation, statistics, or applied maths)
  • Comfortable working with messy, real-world datasets and constraints

Nice to Have

  • Experience modelling energy systems (power, heat, renewables, flexibility)
  • Exposure to infrastructure, utilities, or climate/energy projects
  • Experience with spatial/GIS data
  • Familiarity with energy markets or policy environments

Why Join?

  • Deeply technical role with real-world impact
  • Work on optimisation problems that directly shape decarbonisation strategies
  • Remote-first environment with flexibility
  • High-calibre, engineering-led team
  • Visa sponsorship available

If you’re someone who enjoys getting into the weeds of algorithms, optimisation, and Python-based modelling — and wants your work to drive tangible climate outcomes — this is a standout opportunity.

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Taylor Keenan
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