
Unlocking Sustainability: Advanced Energy Systems Expert
3 days ago
About the Position:
We are seeking a Senior Energy Systems Data Scientist to lead our team in advancing renewable energy and green iron initiatives. As a key member of our data science function, you will play a pivotal role in driving innovation and delivering insights that inform strategic decisions and project design.
- Develop advanced simulation and machine learning-driven frameworks for renewable energy and green iron.
- Mentor and guide teams in modelling, data quality, and uncertainty management.
- Translate technical insights into clear recommendations for senior leaders.
- Create hybrid models combining simulation, optimisation, and machine learning.
- Apply machine learning to speed up simulations, identify cost drivers, and optimise systems.
- Build models linking renewable energy, hydrogen, electrolysers, and green iron production.
- Integrate engineering, cost, and financial data into unified decision-support tools.
- Run scenario analyses and sensitivity studies to guide investment and delivery.
- Drive innovation with digital twins, surrogate models, reinforcement learning, and partnerships.
Requirements:
- A Doctoral or Master's degree in Data Science, Engineering, Applied Mathematics, Energy Systems, or a related field.
- 8+ years of experience in advanced data science, machine learning, or computational modelling, ideally in energy, resources, or process industries.
- Proven expertise in simulation-based optimisation, surrogate modelling, and large-scale data integration.
- Strong proficiency in C++ and Python.
- Experience with ML frameworks such as TensorFlow, PyTorch, scikit-learn, and OpenAI.
- Familiarity with AWS desired.
- Demonstrated experience linking engineering/physical models with techno-economic analysis.
- Familiarity with renewable energy systems, hydrogen, or metallurgical processes advantageous.
Benefits:
- A safe culture that builds respect, fosters inclusiveness, and values diversity.
- We celebrate individual strengths and encourage team members from all backgrounds to bring their whole selves to work.
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