Data Scientist | Outside IR35 | 6 Months | £400 - £450 | You’ll be joining a multidisciplinary team made up of data scientists, ML engineers, software developers, and subject-matter experts, working together to solve complex problems using advanced analytics. The focus is on applying machine learning techniques to large-scale, real-world datasets — including high-frequency vibration signals, SCADA data, and historical turbine failure records. This is a very hands-on role, centred around building, testing, and implementing models that deliver meaningful, practical insights for wind farm operators. What you’ll be doing: Designing and refining machine learning models to identify, diagnose, and predict faults in wind turbines Using a combination of signal processing, ML, and reliability-focused approaches on operational data Developing probabilistic models to assess component health and predict remaining useful life Turning complex outputs into clear, usable insights for engineering and operational teams Working closely with data and engineering teams to help move models into live environments Supporting validation, testing, and responsible use of AI solutions What we’re looking for: Around 3+ years’ experience in a data science or similar role Strong Python skills, particularly with libraries like NumPy, pandas, and SciPy Experience with ML frameworks such as scikit-learn, TensorFlow, or PyTorch A track record of working with messy, real-world datasets (ideally in industrial settings) Comfortable operating in fast-paced environments with some ambiguity Able to communicate technical findings clearly to non-technical audiences Experience in areas like wind energy, rotating equipment, predictive maintenance, or reliability engineering would be a big advantage — but it’s not essential. If this is a role that suits your skill set and available immediately then please apply for the job advert directly or reach out to me with your CV to (url removed). Data Scientist | Outside IR35 | 6 Months | £400 - £450