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- Tasks: Support digital initiatives by analysing and visualising data, and developing dashboards.
- Company: Join a forward-thinking company focused on digital evolution and data-driven solutions.
- Benefits: Gain hands-on experience, mentorship, and opportunities for professional growth.
- Why this job: Make an impact in the digital space while enhancing your data skills.
- Qualifications: Studying Data Science or related field; basic data analysis skills preferred.
- Other info: Collaborative team environment with a focus on continuous learning and improvement.
The predicted salary is between 20000 - 25000 ÂŁ per year.
We are seeking an undergraduate student who has completed two years of study for a placement year to support the Performance & Digital Solutions Lead on a range of digital and data‑driven initiatives. You will help analyse, visualise, and report asset data, and contribute to the development of low‑code analytical tools and dashboards that deliver timely, accurate insights for site decision‑making.
Your responsibilities:
- Low-code software engineering to develop dashboards and applications using tools such as Power BI and the Microsoft Power Platform.
- Assist in gathering, cleaning, and analysing asset data using tools such as Power BI, AVEVA PI, SAP, and SEEQ, with guidance from the team.
- Support the development, validation, and maintenance of reports and dashboards used to track key performance indicators (KPIs) for operational and central functions, following 4-eyes review practices.
- Help design, test, and improve simple data tools or scripts (e.g. low‑code or Python) to automate routine reporting or data transformation tasks.
- Contribute to Uniper’s COODE (Chief Operating Officer Digital Evolution) initiative by providing input, feedback, and support to local digital engagement activities, in line with our digital strategy.
- Work with internal stakeholders, alongside the team, to understand data needs and assist in delivering practical, well‑documented solutions.
- Support knowledge sharing by maintaining clear documentation of data sources, analysis steps, and tool usage.
- Assist in ongoing digitalisation and process improvement projects as part of the wider team.
Your profile:
- Studying towards a degree in Data Science, Computer Science, Engineering, or a related analytical field.
- Basic proficiency in data analysis tools such as Power BI, Python, Excel, or similar; awareness of platforms such as SAP, AVEVA PI, Copilot, and the Microsoft Power Platform is advantageous but not essential.
- Strong analytical and problem‑solving skills, with an ability to work with structured and unstructured data.
- Good written and verbal communication skills, with the ability to present data clearly to technical and non‑technical audiences.
- Demonstrated interest in digitalisation, data‑driven decision‑making, or continuous improvement initiatives.
- Ability to work independently on defined tasks, collaborate effectively as part of a small team, and work with remote colleagues using digital collaboration tools such as Microsoft Teams.
- Curious, proactive, and open to learning new tools, technologies, and ways of working.
Data Science Analyst Undergraduate in England employer: Uniper
Contact Detail:
Uniper Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science Analyst Undergraduate in England
✨Tip Number 1
Network like a pro! Reach out to current employees or alumni from your university who work in data science. A friendly chat can give you insider info about the company and might even lead to a referral.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Power BI or Python. This will help you stand out during interviews and demonstrate your hands-on experience.
✨Tip Number 3
Prepare for the interview by brushing up on common data analysis questions and tools mentioned in the job description. Practise explaining your thought process clearly, as communication is key in this role.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team.
We think you need these skills to ace Data Science Analyst Undergraduate in England
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the job description. Highlight any relevant projects or coursework in data analysis, low-code tools, or digital initiatives to show us you’re a great fit!
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about data science and how your background aligns with our needs. Share specific examples of your work with tools like Power BI or Python to make your application stand out.
Showcase Your Analytical Skills: In your application, don’t just list your skills—demonstrate them! Include examples of how you've tackled data challenges or contributed to projects, especially those involving dashboards or data visualisation.
Apply Through Our Website: We encourage you to apply directly through our website for a smoother process. It’s the best way for us to receive your application and ensures you don’t miss any important updates from our team!
How to prepare for a job interview at Uniper
✨Know Your Tools
Familiarise yourself with the data analysis tools mentioned in the job description, like Power BI and Python. Be ready to discuss your experience with these tools and how you've used them in your studies or projects.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled analytical challenges in the past. Think about specific instances where you gathered, cleaned, or analysed data, and be ready to explain your thought process and the outcomes.
✨Communicate Clearly
Practice explaining complex data concepts in simple terms. You might be asked to present data to both technical and non-technical audiences, so being able to adapt your communication style is key.
✨Demonstrate Your Curiosity
Express your eagerness to learn new tools and technologies. Share any recent projects or courses you've taken that show your proactive approach to digitalisation and continuous improvement.