Enrolled student: in business informatics, business administration, industrial engineering, information systems, or a comparable programme, available ~20 hours per week for 6 months Strong communicator: you are comfortable approaching busy people, asking questions until things actually add up, and summarizing back what you heard to confirm you got it right Structured and detail-oriented: you notice when step 3 contradicts step 7; your notes are documents other people can work from, not reminders only you understand Business and process judgment: you want to understand why a rule exists and what happens at the edges, not just record the happy path; you can tell the difference between a rule, a habit, and an exception. You look for patterns across cases rather than treating each one in isolation. Clear written English: complete, concise, and neat; you would rather write half a page that is right than three pages that are vague Nice to have: basics of process mapping or flowcharts (e.g. BPMN), familiarity with Confluence or Jira, first exposure to customer service or process improvement work, hands-on experience with a process mining tool (Celonis, Disco, ProM or similar)

As Working Student in the Customer Service Automation Centre of Excellence, you are the front end of our automation pipeline: you talk to the people who run our Customer Service processes today, document how things actually work (not how the slide says they work), and validate every rule and exception until it is build-ready. The quality of your documentation directly determines how fast we automate. This position is part-time (20 hours per week), based in our Berlin office (hybrid model). Process discovery: interview Customer Service agents, team leads, and process owners to capture how refund and service processes really run day to day, including the exceptions and workarounds nobody wrote down Documentation: turn what you learn into standardized, concise process documents – trigger, steps, decision rules, systems touched, exceptions, volumes (following our one-page template in Confluence) Validation: walk each documented process back through its owner, cross-check it against real cases, resolve contradictions, and get explicit sign-off before it is handed to the automation team Business rules capture: express eligibility and handling rules as clean decision tables (if X and Y, then Z) that the Process Intelligence Engineer can implement directly, with every ambiguity flagged rather than glossed over Data-driven process analysis: use our process mining platform (Celonis) to surface hidden bottlenecks, deviations, and volume patterns that interviews alone won''t reveal; bring those findings into your documentation and flag them as automation opportunities Pipeline ownership: maintain the documentation backlog so the automation team always has a queue of validated, build-ready processes; track status from “drafted” to “validated” to “built” Upkeep and cleanup: keep documentation current as processes change, and convert existing legacy documentation (much of it diagram-only) into the standard text-based format