Data Solutions Lead - German, Data Collection Excellence

Amazon Amazon · Big Tech · Gdansk, Poland · Administrative Support

This role focuses on consulting with AGI-DS scientists on ML/Gen AI data collections, managing customer relationships, and driving business value through technical advisory. The lead will transform research objectives into data collection requirements, coordinate delivery, and monitor collection health metrics. While it involves ML data operations and understanding ML workflows, the core function is product management and customer advisory for data solutions, not direct AI model building or research.

What you'd actually do

  1. Drive and document effective ML/GenAI solutions for customer requests, transforming complex research objectives into clear, actionable data collection requirements
  2. Coordinate across teams to ensure seamless delivery and stakeholder alignment
  3. Own relationships with customer scientists, becoming their go-to partner for ML data solutions
  4. Provide consultation on ML workflow capabilities, helping customers maximize value
  5. Monitor and optimize collection health metrics to ensure customer success

Skills

Required

  • CEFR C1+ or equivalent fluency in German language
  • Written and spoken knowledge of English is essential (CEFR B2+)
  • Demonstrated experience in effectively defining optimal data creation strategies and executing them
  • Associate's degree or equivalent work experience
  • 2+ years of experience in ML data operations, with a strong understanding of data annotation/ML workflows and concepts
  • Outstanding customer communication and management skills, especially in technical consultation
  • Ability to translate complex technical concepts into tactical applications

Nice to have

  • Bachelor's degree in Computer Science, Business or a related field
  • Experience with project management
  • Working knowledge of JSON, Command Line, and Python
  • Technical account management experience
  • Background in customer success or solution consulting

What the JD emphasized

  • ML/Gen AI data collections
  • data collection requirements
  • ML workflow capabilities
  • data collection best practices
  • scalability of annotation scenarios