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- Tasks: Join our team to innovate energy market forecasting using machine learning and optimization tools.
- Company: Spencer Scott Ltd is a leader in providing clean energy solutions and values diversity.
- Benefits: Earn up to £75,000 with a 15% bonus, pension contributions, training funds, and team lunches.
- Why this job: Be part of the energy revolution and influence projects in a small, collaborative team.
- Qualifications: Strong Python skills and experience with ML models; knowledge of SQL and GitHub/Azure DevOps preferred.
- Other info: Flexible work environment with only two days in-office for collaboration when needed.
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 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
✨Tip Number 1
Make sure to showcase your experience with energy market forecasting in your conversations. If you have worked on similar projects, be ready to discuss specific challenges you faced and how you overcame them.
✨Tip Number 2
Familiarize yourself with the latest trends in machine learning models relevant to short-term forecasting. Being able to discuss recent advancements or case studies can set you apart during interviews.
✨Tip Number 3
Engage with the community on platforms like GitHub or Azure DevOps. Contributing to open-source projects or showcasing your own work can demonstrate your technical skills and passion for data science.
✨Tip Number 4
Prepare to discuss how you can contribute to a small team environment. Highlight your ability to collaborate effectively and influence project outcomes, as this is highly valued in their company culture.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Highlight Relevant Experience: Make sure to emphasize your experience in energy market forecasting and any relevant projects you've worked on. Tailor your CV to showcase your background in data science or data analysis, particularly focusing on short-term forecasting.
Showcase Technical Skills: Clearly list your technical skills, especially your proficiency in Python, machine learning models (like TensorFlow and scikit-learn), SQL, and any experience with GitHub or Azure DevOps. Provide examples of how you've applied these skills in previous roles.
Craft a Compelling Cover Letter: Write a cover letter that reflects your passion for the energy sector and your desire to contribute to sustainable solutions. Mention why you are excited about the opportunity to work in a small team where you can have a significant impact.
Proofread Your Application: Before submitting, carefully proofread your application materials for any errors or typos. A polished application demonstrates attention to detail and professionalism, which are crucial in the data science field.
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
Since the role involves energy market forecasting, familiarize yourself with current trends and challenges in the energy sector. Discuss how your background in data science or analysis can contribute to innovative solutions in this field.
✨Emphasize Collaboration and Influence
The company values small team sizes and individual influence on projects. Share examples from your past experiences where you successfully collaborated with a team and made a significant impact on project outcomes.
✨Prepare Questions About Company Culture
Given the relaxed atmosphere and focus on sustainability, prepare thoughtful questions about the company's culture and values. This shows your genuine interest in being part of their mission to drive innovation for a sustainable future.
