Senior Energy Systems Data Scientist
About the Role:
We are seeking a Senior Energy Systems Data Scientist to lead our team in advancing our 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.
Key Responsibilities:
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:
PhD 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:
We offer 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.