Build bottom-up models from first principles to calculate bespoke decarbonisation levers at scale, accounting for cost, dependencies and implementation time
Quantify energy and material efficiency opportunities, including heat recovery, electrification, utilities, yield losses, material substitution and circular design
Identify Best Available Technologies for technology-specific cases
Develop techno-economic analyses covering CAPEX, OPEX, cost of abatement, marginal abatement cost curves and sensitivity analysis
Develop the carbon pricing engine across compliance markets, taxation, internal shadow pricing and CBAM
Model client exposure under different carbon price scenarios
Identify value from decarbonisation, including green-premium pricing for low-carbon products and incentives or green finance
Write clear, reproducible Python for the models
Mentor junior engineers
Work across industrial sectors including jet engine production, electricity transmission and EV battery manufacturing
Requirements
Masters or PhD in Industrial, Chemical, Process or Mechanical Engineering
3+ years of industry or research experience in techno-economic modelling, with a strong focus on energy and material efficiency and emissions reduction
Proven system-level thinking
Deep working knowledge of energy and material efficiency in industry: heat integration, electrification and fuel switching, and material flows, yield losses and substitution
Strong command of carbon accounting and life cycle assessment, including Scope 1, 2 and 3 inventories, product carbon footprints and relevant frameworks (GHG Protocol, ISO 14064 / 14067, SBTi, CBAM)
Costing proficiency across techno-economic analysis, project finance and carbon pricing
Expert Python for quantitative modelling, including pandas and NumPy
Reproducible, validated and version-controlled models using Git/GitHub
Familiarity with LLMs and agentic-AI workflows
Outstanding communication skills for technical and non-technical audiences
Experience with process simulation software such as Aspen Plus or HYSYS (preferred)
Experience building marginal abatement cost curves or decarbonisation roadmaps for large industrial clients (preferred)
Knowledge of optimisation or machine learning applied to process optimisation and emissions reduction (preferred)
Core Competencies
Demonstrates expertise in techno-economic modeling, carbon accounting, and energy efficiency, with a strong focus on developing reproducible Python models and mentoring junior engineers. Proficient in analyzing decarbonization strategies across various industrial sectors, leveraging advanced analytical tools and frameworks.
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