Data Scientist

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 Num Py, pandas, and Sci Py
• Experience with ML frameworks such as scikit-learn, Tensor Flow, or Py Torch
• 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 .Data Scientist Outside IR35 6 Months £400 - £450