The Role
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.
Key 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 You
- 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
Experience within wind energy, rotating machinery, condition monitoring or reliability engineering is highly desirable, but not essential.
Location: Nottingham, GB
Type: Contract
Department: Advanced Analytics
#J-18808-Ljbffr