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- Tasks: Develop forecasting models and optimise trading algorithms using machine learning.
- Company: Leading renewable energy company focused on innovation and sustainability.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Why this job: Shape the future of energy markets while working with cutting-edge technology.
- Qualifications: Strong Python skills and experience in a fast-paced startup environment.
- Other info: Join a dynamic team passionate about renewable energy and collaboration.
The predicted salary is between 36000 - 60000 £ per year.
A leading renewable energy company is seeking a Data Scientist to develop forecasting and analytical models essential for their trading platform. This role involves creating time-series models for generation and price forecasting, applying machine learning for optimising marketplace algorithms, and collaborating across engineering, product, and commercial teams.
Candidates should possess strong expertise in Python and have experience in a fast-paced startup environment. Joining this dynamic team provides an exciting opportunity to shape the future of energy markets.
Energy Trading Data Scientist — Forecasting & Optimisation employer: The Green Recruitment Company
Contact Detail:
The Green Recruitment Company Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Energy Trading Data Scientist — Forecasting & Optimisation
✨Tip Number 1
Network like a pro! Reach out to people in the renewable energy sector, especially those working in data science. A friendly chat can lead to insider info about job openings and even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your forecasting models and machine learning projects. This will give potential employers a taste of what you can bring to their trading platform.
✨Tip Number 3
Prepare for interviews by brushing up on your Python skills and understanding the latest trends in energy trading. We want you to be ready to impress with your knowledge and problem-solving abilities!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about joining our dynamic team.
We think you need these skills to ace Energy Trading Data Scientist — Forecasting & Optimisation
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your expertise in Python and any relevant experience with time-series models. We want to see how your skills can contribute to our trading platform!
Tailor Your Application: Don’t just send a generic CV! Customise your application to reflect the specific requirements of the Energy Trading Data Scientist role. We love seeing candidates who take the time to connect their experience with what we’re looking for.
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate clarity, so make sure your points are easy to understand and directly related to the job description.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right team!
How to prepare for a job interview at The Green Recruitment Company
✨Know Your Models
Make sure you brush up on your time-series forecasting and machine learning models. Be ready to discuss specific algorithms you've used in the past, how they performed, and any challenges you faced. This shows you not only understand the theory but also have practical experience.
✨Showcase Your Python Skills
Since strong expertise in Python is a must, prepare to demonstrate your coding skills. You might be asked to solve a problem on the spot or explain your previous projects. Practise coding challenges related to data manipulation and model building to feel confident.
✨Understand the Energy Market
Familiarise yourself with current trends in renewable energy and trading platforms. Being able to discuss how your work can impact the energy market will impress the interviewers. They want to see that you're not just a data scientist, but someone who understands the industry.
✨Collaboration is Key
This role involves working with various teams, so be prepared to talk about your experience collaborating with engineering, product, and commercial teams. Share examples of how you’ve successfully worked in cross-functional teams to achieve common goals.
