Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Join us as a Data Scientist to innovate in energy market forecasting using machine learning.
- Company: Be part of a leading company driving the energy revolution for a sustainable future.
- Benefits: Enjoy a competitive salary, 15% bonus, 7% pension, training fund, and fun team lunches.
- Why this job: Make a real impact in a small team where your voice matters and projects are exciting.
- Qualifications: Strong Python skills and experience with ML models like TensorFlow; SQL knowledge is a plus.
- Other info: Flexible work environment with collaboration only when it adds value; we celebrate diversity!
The predicted salary is between 45000 - 105000 £ per year.
Experience working on energy market forecasting?
You’ll be working across the company’s suite of short-term forecasting tools, which has been built by a combination of machine-learning, optimisation and fundamental models within the short-term trading space. The team are relaxed about your background and happy to consider someone from either a Data Scientist or Data Analyst history.
The team are at the forefront of the energy revolution, driving innovation to power a sustainable future. Delivering reliable, affordable, and clean energy solutions to customers while reducing our environmental footprint.
The business is already a well established leader within their domain. However, they like to keep team sizes quite small as they want people to have a major say and influence on projects.
Technical Skills:
Python – strong knowledge required
Experience working across a range of ML models, e.g. TensorFlow and scikit-learn
Commercial experience working on short-term forecasting markets, across either energy, power or financial markets.
GitHub or Azure DevOps knowledge is desired
SQL knowledge is desired
The successful Data Scientist will earn up to 75,000 and in addition there are exceptional benefits which come as part of the overall package including: 15% Bonus, 7% Pension contribution, training fund, weekly team lunches, travel loans and numerous soft leisurely benefits. The team tends to come together 2 days a week for some collaboration, but only when it adds value to do so.
Spencer Scott Ltd is an equal opportunity Recruitment Agency, which means we do not discriminate on the basis of race, colour, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression. We celebrate diversity and are committed to create inclusive working environments for all our clients.
Data scientist (marketing) employer: Spencer Scott - Technology Recruitment
Contact Detail:
Spencer Scott - Technology Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data scientist (marketing)
✨Tip Number 1
Familiarize yourself with the specific forecasting tools used in the energy market. Understanding how machine learning and optimization models are applied in this context will give you a significant edge during discussions.
✨Tip Number 2
Showcase your experience with Python and relevant ML frameworks like TensorFlow and scikit-learn. Be prepared to discuss specific projects where you've successfully implemented these technologies.
✨Tip Number 3
Highlight any commercial experience you have in short-term forecasting markets, especially in energy or financial sectors. This will demonstrate your practical knowledge and relevance to the role.
✨Tip Number 4
Engage with the company's values around sustainability and innovation. Being able to articulate how your personal values align with their mission can make a strong impression during interviews.
We think you need these skills to ace Data scientist (marketing)
Some tips for your application 🫡
Highlight Relevant Experience: Make sure to emphasize any experience you have in energy market forecasting or related fields. Discuss specific projects where you've applied machine learning models, especially in short-term forecasting.
Showcase Technical Skills: Clearly outline your proficiency in Python and any experience with ML frameworks like TensorFlow and scikit-learn. Mention your familiarity with SQL and version control systems like GitHub or Azure DevOps.
Tailor Your CV: Customize your CV to reflect the skills and experiences that align with the job description. Use keywords from the job posting to ensure your application stands out to recruiters.
Craft a Compelling Cover Letter: Write a cover letter that not only summarizes your qualifications but also expresses your passion for the energy sector and your desire to contribute to sustainable solutions. Make it personal and engaging.
How to prepare for a job interview at Spencer Scott - Technology Recruitment
✨Showcase Your Technical Skills
Make sure to highlight your strong knowledge of Python and any experience you have with machine learning models like TensorFlow and scikit-learn. Be prepared to discuss specific projects where you've applied these skills, especially in the context of short-term forecasting.
✨Demonstrate Industry Knowledge
Familiarize yourself with the energy market and its forecasting challenges. Discuss any relevant experience you have in energy, power, or financial markets, and how it relates to the role. This will show that you understand the industry and can contribute effectively.
✨Emphasize Collaboration
Since the team values collaboration, be ready to talk about your experiences working in small teams. Share examples of how you've influenced projects and contributed to team success, as this aligns with their preference for a close-knit working environment.
✨Prepare Questions
Have thoughtful questions ready about the company's forecasting tools and their approach to innovation in the energy sector. This not only shows your interest in the role but also gives you insight into how you can fit into their vision for a sustainable future.
