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 for professional growth.
- Other info: Join a dynamic team dedicated to tackling real-world energy challenges.
- Why this job: Make a difference in the renewable energy sector 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.
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.
Fully Remote Data 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, and ample 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 a rapidly evolving sector. Join us in shaping the future of energy and enjoy the benefits of working in a supportive environment that values your contributions.
StudySmarter Expert Advice🤫
We think this is how you could land Fully Remote Data
✨Tip Number 1
Network like a pro! Reach out to people in the renewable energy sector on LinkedIn or at industry events. 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 data analysis and modelling projects. Use GitHub to share your code and visualisations, making it easy for potential employers to see what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with Python, optimisation techniques, and how you’ve tackled real-world data challenges in the past.
✨Tip Number 4
Don’t forget to apply through our website! We’re always looking for passionate individuals who want to make a difference in the renewable energy space. Your next big opportunity could be just a click away!
We think you need these skills to ace Fully Remote Data
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of Data & Modelling Analyst. Highlight your experience with Python, data analysis, and any relevant projects in renewable energy. We want to see how your skills fit our needs!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about renewable energy and how your background makes you a perfect fit for this role. Let us know what excites you about working with us!
Showcase Your Technical Skills:Don’t hold back on showcasing your technical prowess! Mention your experience with optimisation modelling, data visualisation, and any tools like Power BI or SQL. We love seeing candidates who can hit the ground running!
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep everything organised and ensures your application gets the attention it deserves. We can't wait to hear from you!
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 previous roles.
✨Show Off Your Python Skills
Since strong Python skills are a must, prepare to demonstrate your proficiency. Bring along examples of optimisation models or data visualisations you've created using libraries like pandas and NumPy. If you can, walk through a coding challenge or a project that highlights your technical 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 scenarios where you successfully communicated intricate modelling insights to clients or team members who weren’t as technically savvy.
✨Be Ready for Scenario Analysis
Expect questions about scenario analysis and strategic recommendations. Think of past projects where you contributed to decision-making processes in renewable energy. Be prepared to discuss how you approached these analyses and the impact they had on the project outcomes.
