At a Glance
- Tasks: Analyse large datasets and build optimisation models to support renewable energy projects.
- Company: Specialist renewable energy advisory firm with a focus on sustainability.
- Benefits: Competitive salary, hybrid working, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovative energy solutions.
- Why this job: Make a real impact in the transition to renewable energy while honing your analytical skills.
- Qualifications: 3 years of experience in data analysis, strong Python skills, and knowledge of energy systems.
The predicted salary is between 40000 - 50000 € per year.
A specialist renewable energy advisory firm is hiring a Data & Modelling Analyst to support quantitative analysis and modelling across major energy and infrastructure projects. This is a highly analytical role focused on energy systems, optimisation modelling and data-driven decision making. You will work closely with developers, utilities, investors and government bodies on projects related to renewable energy, storage, market design and decarbonisation.
Salary: Competitive, dependent on experience
Location: London, hybrid working (typically once per week onsite or less)
What you’ll be doing:
- Prepare, structure and analyse large datasets across energy markets, grid systems and policy scenarios
- Build and run mathematical optimisation and simulation models using Python
- Support analysis across areas such as storage optimisation, dispatch modelling and market simulations
- Develop dashboards, notebooks and reporting outputs to communicate modelling insights clearly
- Contribute to scenario analysis and strategic recommendations for clients across the renewable energy sector
- Work closely with senior consultants and external stakeholders on complex analytical projects
- Help improve reproducibility, data workflows and modelling processes across the business
What you’ll need:
- Around 3 years’ commercial experience within data analysis, modelling or energy analytics
- Strong Python skills including pandas, NumPy, SciPy and data visualisation libraries
- Experience with mathematical optimisation or modelling techniques such as LP/MILP
- Understanding of electricity markets, power systems or renewable energy environments
- Experience with Power BI and basic SQL
- Comfortable working with large, imperfect real-world datasets
- Ability to explain complex analytical findings to non-technical stakeholders
- Self-sufficient and organised working style
Nice to have:
- Experience within energy modelling, storage optimisation or decarbonisation projects
- Understanding of machine learning concepts or forecasting models
- Familiarity with Git and collaborative coding workflows
- Interest in renewable energy, climate technology and energy transition projects
This role would suit someone who enjoys combining technical modelling skills with real-world energy challenges, and who wants to contribute to projects supporting the transition to renewable energy.
Data Quality employer: Digital Waffle
As a leading renewable energy advisory firm, we pride ourselves on fostering a collaborative and innovative work culture that empowers our employees to make a meaningful impact in the transition to sustainable energy. With competitive salaries, flexible hybrid working arrangements in London, and ample opportunities for professional growth, we support our team members in developing their skills while working on cutting-edge projects alongside industry experts. Join us to be part of a mission-driven organisation that values your contributions and encourages a passion for renewable energy and climate technology.
StudySmarter Expert Advice🤫
We think this is how you could land Data Quality
✨Tip Number 1
Network like a pro! Reach out to people in the renewable energy sector on LinkedIn or at industry events. We can’t stress enough how valuable personal connections can be in landing that Data & Modelling Analyst role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python projects, especially those involving optimisation and data visualisation. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your knowledge of electricity markets and power systems. We recommend practising common interview questions related to data analysis and modelling to boost your confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Data Quality
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data & Modelling Analyst role. Highlight your experience with Python, data analysis, and any relevant projects in renewable energy. We want to see how your skills match what we're looking for!
Showcase Your Skills:In your application, don’t just list your skills—show us how you've used them! Whether it's building optimisation models or working with large datasets, give us examples that demonstrate your expertise and problem-solving abilities.
Be Clear and Concise:When writing your cover letter, keep it clear and to the point. Explain why you're passionate about renewable energy and how your background makes you a great fit for our team. We appreciate straightforward communication!
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll find all the details you need right there. Let’s make this happen together!
How to prepare for a job interview at Digital Waffle
✨Know Your Data Inside Out
Make sure you’re familiar with the datasets relevant to the role. Brush up on your experience with large, imperfect datasets and be ready to discuss how you've handled them in the past. This will show your analytical skills and understanding of real-world challenges.
✨Show Off Your Python Skills
Prepare to demonstrate your Python expertise, especially with libraries like pandas, NumPy, and SciPy. You might be asked to solve a problem or explain a model you've built, so have examples ready that highlight your coding prowess and optimisation techniques.
✨Communicate Clearly
Since you'll need to explain complex findings to non-technical stakeholders, practice simplifying your explanations. Think about how you can convey your insights from modelling and analysis in a way that's easy to understand, perhaps using visuals or dashboards as examples.
✨Stay Current on Energy Trends
Familiarise yourself with the latest trends in renewable energy, storage optimisation, and decarbonisation. Being able to discuss current events or innovations in the sector will demonstrate your passion and commitment to the field, making you a more attractive candidate.
