At a Glance
- Tasks: Join a team to design and implement machine learning models for wind turbine diagnostics.
- Company: Dynamic company focused on advanced analytics in renewable energy.
- Benefits: Competitive pay, hands-on experience, and the chance to work with cutting-edge technology.
- Other info: Fast-paced environment with opportunities for growth and innovation.
- Why this job: Make a real impact in renewable energy while developing your data science skills.
- Qualifications: 3+ years in data science, strong Python skills, and experience with ML frameworks.
The predicted salary is between 40000 - 45000 € per year.
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.
Data Scientist in Nottingham employer: Opus Recruitment Solutions Ltd
Join a forward-thinking company that values innovation and collaboration, where you'll work alongside a diverse team of experts in a dynamic environment focused on solving real-world challenges in the wind energy sector. With a commitment to employee growth, you will have access to continuous learning opportunities and the chance to make a tangible impact through your work. Located in a vibrant area, this role offers not just competitive compensation but also the chance to be part of a mission-driven organisation dedicated to sustainability and technological advancement.
Contact Detail:
Opus Recruitment Solutions Ltd Recruiting Team
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist in Nottingham
✨Tip Number 1
Network like a pro! Reach out to your connections in the data science field, especially those who work with machine learning or in the wind energy sector. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python and machine learning frameworks. This is your chance to demonstrate how you’ve tackled real-world datasets and delivered insights.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to explain complex concepts in simple terms, as you’ll need to communicate effectively with non-technical teams.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace Data Scientist in Nottingham
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience in data science and machine learning. We want to see how your skills align with the role, so don’t be shy about showcasing your Python prowess and any relevant projects you've worked on.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data science and how you can contribute to our multidisciplinary team. Keep it concise but impactful – we love a good story!
Showcase Real-World Experience:If you've worked with messy datasets or in industrial settings, make sure to mention that! We’re keen on seeing how you’ve tackled real-world problems, especially if it relates to wind energy or predictive maintenance.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy – just a few clicks and you’re done!
How to prepare for a job interview at Opus Recruitment Solutions Ltd
✨Know Your Data Science Stuff
Make sure you brush up on your data science fundamentals, especially around machine learning models and Python libraries like NumPy and pandas. Be ready to discuss your past projects and how you've tackled messy datasets, as this will show your hands-on experience.
✨Showcase Your Problem-Solving Skills
Prepare to talk about specific problems you've solved using advanced analytics. Think of examples where you've designed or refined models to predict faults or assess component health. This will demonstrate your ability to apply theory to real-world scenarios.
✨Communicate Clearly
Since you'll need to explain complex findings to non-technical audiences, practice simplifying your explanations. Use analogies or straightforward language to convey your insights, making it easier for everyone to understand the value of your work.
✨Be Ready for Technical Questions
Expect some technical questions related to machine learning frameworks like TensorFlow or PyTorch. Brush up on your knowledge of these tools and be prepared to discuss their applications in your previous roles, especially in fast-paced environments.
