Role overview
You will work with a cross‑functional team of Data Scientists, ML Engineers, Software Developers and domain experts, applying advanced analytics and machine‑learning techniques to large, real‑world datasets. This includes high‑frequency vibration data, SCADA data, and recorded turbine failure data.
The focus of this contract is hands‑on delivery — developing, validating and deploying models that generate actionable insights for wind‑farm owners and operators.
Responsibilities
- Develop and optimise AI‑driven algorithms to detect, diagnose and predict wind‑turbine failure modes
- Apply signal‑processing, reliability‑engineering and machine‑learning techniques to real operational data
- Build probabilistic models to estimate remaining useful life (RUL) and component failure risk
- Translate analytical outputs into clear, actionable insights for engineers and operational stakeholders
- Collaborate closely with engineers and data teams to support deployment into production environments
- Contribute to model validation, testing and responsible‑AI practices
About the company
- 3+ years' experience as a Data Scientist or similar role
- Strong Python skills (NumPy, pandas, SciPy) and experience with ML frameworks such as scikit‑learn, TensorFlow or PyTorch
- Experience working with complex, real‑world industrial datasets
- Comfortable working at pace and dealing with ambiguous problems
- Able to clearly communicate technical findings to non‑technical stakeholders
Tags & focus areas
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