Working Student (m/f/d) Quality Process Automation and Digitalization

Lüneburg
Part-time
Education
Student

WHAT WE OFFER
  • Modern development tools and methodologies

  • A collegial and sustainability-oriented working environment

  • Work in a young and agile development team

  • Insight into various facets of development through diverse and practical work packages

  • Flexible working hours and appropriate compensation

  • Health promotion through Hansefit

  • Subsidies for the Deutschlandticket (Germany Ticket)

  • Employee discounts, company events, and on-site parking

YOUR RESPONSIBILITIES
  • Support the Quality Department in efficiency and continuous improvement initiatives across processes and tools

  • Analyze existing business and quality processes to identify automation and optimization potential

  • Design and develop custom digital solutions that align with employee needs and real process requirements (main focus)

  • Support the implementation of automation and AI-based concepts in quality-related workflows

  • Collaborate with quality engineers and process owners to translate requirements into technical solutions

  • Assist in data preparation, validation, and analysis for quality and compliance use cases

  • Document developed solutions, concepts, and learnings to enable sustainable use and future scaling

WHAT WE ARE LOOKING FOR
  • Ongoing studies in a technical field (e.g. engineering, computer science, data science, industrial engineering, or similar)

  • Programming experience, ideally with Python (e.g. scripting, data processing, automation)

  • Basic understanding of business processes and structured problem-solving

  • Interest in process automation, digitalization, and AI applications

  • Ability to work independently and analytically with a hands-on mindset

  • Good communication skills and the ability to work with cross-functional teams

POSSIBLE PROJECTS YOU MAY WORK ON
  • AI-supported review and validation of requirements (e.g. consistency, completeness, compliance checks)

  • Automated creation and verification of failure analysis reports (e.g. FMEA-related data processing)

  • Automated verification and plausibility checks of supplier documentation

  • Prototyping internal tools to improve quality transparency and decision-making