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For Companies At a Glance
- Tasks: Design and build machine learning models to tackle real-world challenges.
- Company: Join a fast-growing team at the forefront of data science and AI.
- Benefits: Enjoy a competitive salary, hybrid working, and additional perks like private healthcare.
- Why this job: Make a meaningful impact while collaborating with experts in a supportive culture.
- Qualifications: Must have a Master’s degree in a relevant field and strong Python skills.
- Other info: This role is ideal for recent graduates eager to apply their knowledge.
The predicted salary is between 28000 - 36000 £ per year.
Junior Data Scientist – Renewable Energy Asset Performance
Location: London (Hybrid – 3 days in office)
Salary: £40,000 – £50,000 + Bonus Up to 40% + Benefits
Start Date: ASAP (must be available to start in February)
The opportunity
I’m recruiting for a fast-growing renewable energy asset owner/operator with a rapidly expanding portfolio of onsite solar PV projects across the UK. They’re looking for a junior Data Analyst / Data Scientist to help drive portfolio performance, strengthen investor-grade reporting, and build analytics tools that improve decision-making across the business.
This is a high-impact role where you’ll work with real operational and financial data, partner closely with asset management and operations, and see your work directly influence performance outcomes.
What you’ll work on
- Analyse and monitor asset and portfolio performance (generation, availability, efficiency, losses, uptime, incident trends)
- Identify underperformance, anomalies, and emerging risks — quantify impact and support corrective actions
- Build and maintain KPIs, benchmarks, and performance thresholds at asset and portfolio level
- Produce weekly/monthly/quarterly performance reporting for internal stakeholders and investors
- Develop dashboards and internal tools (portfolio health views, incident tracking, loss attribution, performance deep-dives)
- Improve automation and data quality to reduce manual reporting and increase reliability
- Support forecasting and scenario analysis for operations and new projects
- Contribute to practical AI/ML use-cases that streamline workflows and enhance insight generation
What makes this role different
- Production analytics mindset: you’ll build outputs that stakeholders actually use, not “analysis for analysis’ sake”
- Ownership early: you’ll take responsibility for meaningful parts of reporting and performance analytics quickly
- End-to-end exposure: operations + asset management + finance, so you learn the full renewable asset lifecycle
- Strong development runway: mentorship, feedback, and the chance to grow into more advanced modelling and automation
What we’re looking for
- A completed degree in Data Science, Computer Science, Mathematics, Physics, Engineering, or similar
- 1-3 years experience in Data Analytics or Data Science across internships and/or work experience
- Strong Python skills for analysis (pandas/NumPy, clean coding practices)
- Solid understanding of statistics, experimentation/evaluation, and working with messy real-world data
- Confident using SQL to query and combine datasets
- Clear communicator who can turn analysis into actionable recommendations
- Strong attention to detail and pride in high-quality outputs
- Immediately available to start (or available within a very short notice period)
- Full right to work in the UK (no visa sponsorship available)
🏢 Hybrid working (Central London – 2/3 days in office)
📈 Mentorship + progression: structured development and regular feedback
🛠 Modern tooling and scope to automate/improve how things are done
How to apply
Send your most up-to-date CV and a quick note confirming your availability to start ASAP. I’ll arrange an initial call immediately.
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Contact Detail:
Intellect Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Junior Data Scientist
✨Tip Number 1
Network with professionals in the data science field, especially those who work at StudySmarter or similar companies. Attend industry meetups, webinars, or conferences to make connections and learn more about the role.
✨Tip Number 2
Showcase your projects on platforms like GitHub or personal websites. Highlight any machine learning models or data analysis projects you've completed during your Master's, as this will demonstrate your practical skills and passion for the field.
✨Tip Number 3
Prepare to discuss your understanding of machine learning concepts and your experience with Python and SQL during interviews. Be ready to explain how you've applied these skills in real-world scenarios or academic projects.
✨Tip Number 4
Stay updated on the latest trends in data science and AI. Being knowledgeable about recent advancements can help you engage in meaningful discussions during interviews and show your enthusiasm for continuous learning.
We think you need these skills to ace Junior Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant skills and experiences that align with the Junior Data Scientist role. Emphasise your programming skills in Python, any projects involving machine learning, and your academic achievements.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data science and your eagerness to solve real-world problems. Mention specific projects or experiences that demonstrate your understanding of machine learning concepts and your ability to collaborate effectively.
Highlight Relevant Coursework: In your application, include any relevant coursework from your Master’s degree that pertains to data science, machine learning, or statistics. This will help demonstrate your academic foundation and readiness for the role.
Showcase Communication Skills: Since the role involves presenting findings to both technical and non-technical stakeholders, provide examples in your application of how you've effectively communicated complex ideas in the past, whether through presentations, reports, or collaborative projects.
How to prepare for a job interview at Intellect Group
✨Showcase Your Technical Skills
Be prepared to discuss your programming skills in Python and any experience you have with libraries like NumPy, pandas, and scikit-learn. Bring examples of projects or coursework where you've applied these skills, as this will demonstrate your practical knowledge.
✨Understand the Role's Requirements
Familiarise yourself with the core responsibilities of a Junior Data Scientist. Be ready to explain how your academic background and any relevant experience align with tasks such as data cleaning, model building, and presenting findings to stakeholders.
✨Prepare for Problem-Solving Questions
Expect to face questions that assess your problem-solving abilities. Practice explaining your thought process when tackling complex datasets or designing machine learning models, as this will highlight your analytical skills and creativity.
✨Demonstrate Your Passion for Learning
Convey your enthusiasm for staying current with advancements in data science and AI. Share any recent articles, courses, or projects that showcase your commitment to continuous learning and how you plan to contribute new ideas to the team.
