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- Tasks: Join us as a Marketing 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 are essential.
- Other info: We value diversity and create inclusive environments for everyone.
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.
Marketing 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 Marketing Data Scientist
✨Tip Number 1
Make sure to showcase your experience with energy market forecasting during networking events or informal meetups. Engaging with professionals in the field can help you gain insights and potentially lead to referrals.
✨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
Join online communities or forums focused on data science and energy markets. Participating in discussions can enhance your knowledge and help you connect with others who might have leads on job openings.
✨Tip Number 4
Consider contributing to open-source projects related to forecasting tools on platforms like GitHub. This not only builds your portfolio but also demonstrates your practical skills to potential employers.
We think you need these skills to ace Marketing 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 and any experience with machine learning models like TensorFlow and scikit-learn. Mention your familiarity with GitHub or Azure DevOps and SQL, as these are important for the role.
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. Discuss how your skills align with the company's mission and how you can add value to their small team.
Proofread Your Application: Before submitting, carefully proofread your application materials. Check for any grammatical errors or typos, and ensure that all information is accurate and presented clearly. A polished application reflects your attention to detail.
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're not just technically proficient but also understand the industry landscape.
✨Emphasize Collaboration and Teamwork
Since the team values small sizes and collaboration, be ready to talk about your experiences working in small teams. Share examples of how you've contributed to projects and influenced outcomes, as this aligns with their culture of having a major say in projects.
✨Prepare Questions About Company Culture
The company prides itself on being at the forefront of the energy revolution and values diversity. Prepare thoughtful questions about their approach to innovation and inclusivity. This shows your genuine interest in their mission and values, making you a more attractive candidate.
