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- Tasks: Join us as a Tech Data Scientist, working on innovative energy market forecasting tools.
- 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 innovation thrives.
- 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.
Tech 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 Tech Data Scientist
✨Tip Number 1
Make sure to showcase your experience with energy market forecasting during any discussions. Highlight specific projects where you've applied machine learning models, as this will resonate well with the team’s focus on innovation in the energy sector.
✨Tip Number 2
Familiarize yourself with the latest trends in short-term forecasting tools and how they apply to the energy market. Being able to discuss these trends and their implications can set you apart as a knowledgeable candidate.
✨Tip Number 3
Engage with the community on platforms like GitHub or Azure DevOps. Contributing to relevant projects or showcasing your own work can demonstrate your technical skills and passion for data science in the energy sector.
✨Tip Number 4
Prepare to discuss your experience with Python and SQL in detail. Be ready to provide examples of how you've used these languages in past projects, especially in relation to machine learning and forecasting.
We think you need these skills to ace Tech 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. Mention specific machine learning models you've used, such as TensorFlow or scikit-learn, to showcase your technical skills.
Showcase Technical Skills: Clearly outline your proficiency in Python, SQL, and any experience with GitHub or Azure DevOps. Providing examples of how you've applied these skills in previous roles can strengthen your application.
Tailor Your CV: Customize your CV to align with the job description. Focus on your data science or data analyst background and how it relates to short-term forecasting in energy or financial markets.
Craft a Compelling Cover Letter: Write a cover letter that reflects your passion for the energy sector and innovation. Discuss why you want to be part of a small team that influences projects and how you can contribute to their mission of delivering clean energy solutions.
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 energy market forecasting.
✨Demonstrate Your Understanding of Short-Term Forecasting
Since the role focuses on short-term forecasting tools, be ready to explain your experience in this area. Discuss any relevant commercial experience you have in energy, power, or financial markets, and how it relates to the company's goals.
✨Emphasize Collaboration and Teamwork
The company values small team sizes and collaboration. Share examples of how you've successfully worked in teams, contributed to projects, and influenced outcomes. This will show that you can thrive in their collaborative environment.
✨Prepare Questions About Company Culture
Since the company promotes a relaxed atmosphere and values diversity, prepare thoughtful questions about their culture and how they support innovation. This shows your interest in not just the role, but also in being part of their mission to drive a sustainable future.
