At a Glance
- Tasks: Develop AI algorithms to predict wind-turbine failures and generate actionable insights.
- Company: Leading firm in renewable energy with a focus on innovation.
- Benefits: Competitive pay, flexible working hours, and opportunities for professional growth.
- Other info: Collaborative team environment with exciting projects in wind energy.
- Why this job: Make a real impact in the renewable energy sector while honing your data science skills.
- Qualifications: 3+ years in data science, strong Python skills, and experience with ML frameworks.
The predicted salary is between 50000 - 65000 € per year.
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
Data Scientist in Nottingham employer: Gofractional
Join a forward-thinking company in Nottingham that champions innovation and collaboration, where Data Scientists thrive in a dynamic work culture. With a strong emphasis on employee growth, you will have access to cutting-edge projects in the wind energy sector, alongside opportunities for professional development and hands-on experience with real-world datasets. Enjoy a supportive environment that values your contributions and fosters meaningful insights for sustainable energy solutions.
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 professionals in the wind energy and data science fields on LinkedIn. Join relevant groups, attend webinars, and don’t be shy about asking for informational interviews. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving machine learning and real-world datasets. Use platforms like GitHub to share your code and insights. This will give potential employers a taste of what you can do!
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and problem-solving abilities. Practice explaining complex concepts in simple terms, as you'll need to communicate with non-technical stakeholders. Mock interviews can help you get comfortable with this!
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Tailor your application to highlight your experience with Python, machine learning frameworks, and any relevant projects you've worked on.
We think you need these skills to ace Data Scientist in Nottingham
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Scientist role. Highlight your experience with Python, machine learning frameworks, and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
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 your background fits with our focus on wind energy and predictive analytics. Let us know what excites you about this opportunity!
Showcase Your Projects:If you've worked on any interesting projects, especially those involving real-world datasets or machine learning, make sure to mention them. We love seeing practical applications of your skills, so don't hold back!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us that you're keen on joining the StudySmarter team!
How to prepare for a job interview at Gofractional
✨Know Your Data Inside Out
Before the interview, dive deep into the types of datasets mentioned in the job description. Familiarise yourself with high-frequency vibration data and SCADA data. Being able to discuss how you’ve worked with similar datasets or how you would approach them will show your expertise and readiness for the role.
✨Showcase Your Python Skills
Make sure you can confidently talk about your experience with Python, especially libraries like NumPy, pandas, and SciPy. Prepare examples of projects where you used these tools to solve real-world problems, as this will demonstrate your technical proficiency and problem-solving abilities.
✨Communicate Clearly with Non-Technical Stakeholders
Since the role involves translating complex analytical outputs into actionable insights, practice explaining your past projects in simple terms. Think of how you would describe your findings to someone without a technical background, as this will highlight your communication skills and ability to collaborate effectively.
✨Prepare for Hands-On Problem Solving
Expect practical questions that assess your ability to develop and optimise AI-driven algorithms. Brush up on your machine-learning techniques and be ready to discuss how you would apply them to predict wind-turbine failure modes. This hands-on focus is crucial, so think through your approach to real operational data scenarios.
