Working Student – AI Process & Business Excellence (m/f/d)

Those opportunities are then aligned with the team, and an approach is taken to ensure delivery - quantifying the waste, and building or specifying the automation that removes it, using AI tooling and our existing automation platforms. You will be trusted with real processes and real stakeholders from your first weeks. The average day of a Working Student in AI & Business Process Automation The role is divided into 3 key value areas Process analysis: Mapping and reviewing existing business processes across our markets.

You run user interviews with the people doing the work, document the current state, and measure cycle times, handoffs and manual touchpoints. You also look at job titles across the organisation and benchmark them against the market, to understand how those roles have been optimised elsewhere and what that means for us. You will be expected to bring numbers, not opinions.

Automation delivery: Delivering the improvements you have identified, together with the team. Smaller cases you build in-house using our existing toolset (n8n, Google Workspace / AppScript, APIs and our AI tooling). On more complex processes you work alongside experts in the team, learning how larger automations are scoped, specified and delivered.

You test what you build and you measure whether it actually saved anything. AI enablement: Educating colleagues on quick wins and small changes they can make to their own workflow. Not everything needs to be process automation, sometimes it just needs a slight change in user behaviour, and knowing the difference is part of the job.

You will run short enablement sessions, build and refine prompts and internal AI assistants for specific teams, feed back where people struggle so we can improve the tooling, and contribute to our broader AI enablement initiatives across the employee base. Dein Profil You are enrolled at a university for the entire duration of the working student contract, in Industrial Engineering (Wirtschaftsingenieurwesen), Business Informatics, Information Systems, Computer Science, Business Administration with a technical focus, or a comparable field Available for approx. 20 hours per week during the semester First practical experience with process analysis, process modelling (e.g. BPMN) or operational improvement work - from an internship, a working student role or a university project Hands-on experience with AI tooling for real work, not just experimentation.

You can explain what you have actually built or automated with it Experience with, or a strong willingness to quickly learn, no-code/low-code automation platforms (n8n, Make, Zapier or similar) Basic scripting ability - Python, JavaScript/AppScript or similar - and comfort working with APIs and structured data Confident with spreadsheets and data: you can pull a dataset apart and tell us what it says Strong people skills. You can sit with a non-technical colleague, understand their process, and explain a technical solution in language they trust Structured, self-directed working style. You are given problems, not tickets, and you organise yourself accordingly Ability to communicate at a business level in English.

German would be a huge plus. Based in or around Berlin or Hamburg, with willingness to travel on occasion. Benefits You are part of an international, dynamic, and highly motivated team of people who have proven to make things happen With your work, you accelerate the "energy transition" and hence have a direct impact on our climate Work with and learn from other super-smart colleagues with industry experience.

You will enjoy direct contact with core decision-makers You will enjoy the best chances of entering full-time in one of Europe's most thriving scaleups Flexible working hours that fit around your lecture schedule, with hybrid working and offices in Hamburg and Berlin Create a healthy balance alongside your work and enjoy all the benefits of the EGYM Wellpass Benefits and discounts are yours with Futurebens Find more English Speaking Jobs in Germany on Arbeitnow

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Quelle: Statistisches Bundesamt (Destatis), Tabelle; dl-de/by-2-0; eigene Berechnung