Data Science Analyst Undergraduate

Data Science Analyst Undergraduate

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.