At a Glance
- Tasks: Analyse and model data for renewable energy projects using Python and optimisation techniques.
- Company: Specialist renewable energy advisory firm focused on impactful projects.
- Benefits: Competitive salary, hybrid working, and opportunities to work on meaningful energy solutions.
- Other info: Collaborative environment with a focus on professional growth and sustainability.
- Why this job: Join a team tackling real-world energy challenges and drive the transition to renewable energy.
- Qualifications: 3 years' experience in data analysis, strong Python skills, and knowledge of energy systems.
The predicted salary is between 45000 - 55000 € 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 Modeler in London 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, hybrid working arrangements, and opportunities for professional growth, our Data & Modelling Analyst role offers a unique chance to engage with diverse stakeholders while developing cutting-edge analytical solutions in the heart of London. Join us to be part of a team that values your expertise and supports your career development in the dynamic field of renewable energy.
StudySmarter Expert Advice🤫
We think this is how you could land Data Modeler in London
✨Network Like a Pro
Get out there and connect with people in the renewable energy sector! Attend industry events, webinars, or even local meetups. The more you engage with professionals, the better your chances of landing that Data Modeler role.
✨Show Off Your Skills
Create a portfolio showcasing your data analysis and modelling projects. Use GitHub to share your code and visualisations. This will not only demonstrate your Python skills but also your ability to tackle real-world energy challenges.
✨Ace the Interview
Prepare for interviews by brushing up on your knowledge of electricity markets and optimisation techniques. Be ready to explain complex concepts in simple terms, as you'll need to communicate effectively with non-technical stakeholders.
✨Apply Through Our Website
Don't forget to apply directly through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Data Modeler in London
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 Projects:Include specific examples of your work with optimisation models or data visualisation. If you've tackled complex analytical projects, let us know! This helps us understand your hands-on experience and how you can contribute.
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 skills can help us tackle real-world challenges. We appreciate straightforward communication!
Apply Through Our Website:Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can't wait to see what you bring to the table!
How to prepare for a job interview at Digital Waffle
✨Know Your Data Inside Out
Make sure you’re well-versed in the datasets relevant to the role. Brush up on your experience with large datasets, especially in energy markets and grid systems. Be ready to discuss specific examples of how you've structured and analysed data in past projects.
✨Show Off Your Python Skills
Since strong Python skills are a must, prepare to demonstrate your proficiency. Bring along examples of optimisation models or simulations you've built using libraries like pandas and NumPy. You might even want to run through a coding challenge to showcase your abilities.
✨Communicate Complex Ideas Simply
You’ll need to explain your analytical findings to non-technical stakeholders, so practice simplifying complex concepts. Prepare a few examples where you’ve successfully communicated technical information in an accessible way, perhaps through dashboards or reports.
✨Be Ready for Scenario Analysis
Expect questions about scenario analysis and strategic recommendations. Think of instances where you’ve contributed to decision-making processes in renewable energy projects. Highlight your understanding of market design and decarbonisation to show you’re aligned with their goals.
