AI Data Quality Specialist (m/f/d)

Role Summary Job Description As AI Data Quality Specialist (m/f/d), you play a key role in enabling successful AI solutions across MANN+HUMMEL Transportation. Acting as the link between business users and AI teams, you help ensure that data used for AI applications is complete, consistent, and suitable for both model training and productive use.

Working closely with business experts, AI Product Owners, Data Engineers, and AI Quality Assurance specialists, you identify AI-relevant data quality issues, understand their underlying business, process, or system-related causes, and support the implementation of sustainable improvement measures. Through your work, you help create the data foundation required for reliable and scalable AI solutions.

Your Responsibilities

• Collaborate with business users to understand how data is created, maintained, interpreted, and used within daily operations
• Assess data quality, usability, completeness, consistency, and accuracy for AI and machine learning use cases
• Identify AI-relevant data quality gaps and analyze their business-, process-, or system-related root causes
• Translate business data practices and challenges into clear AI-specific data quality requirements
• Coordinate and align cross-functional stakeholders to address AI-related data quality issues
• Support the preparation, validation, and continuous improvement of datasets used for AI model training, testing, and productive AI solutions
• Contribute to the definition of AI-specific data quality rules, validation criteria, and quality measures
• Work closely with AI Product Owners, Data Engineers, AI Quality Assurance specialists, and business experts to resolve data quality challenges
• Document assessments, findings, improvement actions, and best practices to ensure transparency and sustainable implementation
• Conduct knowledge-sharing and enablement activities to strengthen awareness of AI-specific data quality requirements across the organization

Your Profil

• Education: Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Engineering, Information Management, or a comparable field.
• Experience: Experience in AI-related data preparation, data quality assessment, AI enablement, or comparable data-focused roles. Experience working closely with both business users and technical teams in cross-functional environments is required.
• Expertise:

• Understanding of how structured, semi-structured, and unstructured data is used in AI and machine learning applications
• Experience assessing and improving data quality for AI, analytics, digital, or data-driven use cases
• Knowledge of common AI data risks such as missing information, inconsistent labeling, data drift, bias, and data leakage
• Understanding of the AI/ML lifecycle with a particular focus on data preparation, validation, and monitoring
• Basic knowledge of SQL and/or Python for data inspections and quality assessments
• Ability to evaluate whether training data and operational data are suitable for AI applications
• Ability to translate business processes and data usage into actionable AI-relevant insights
• Experience collaborating across business and technical functions within matrix organizations
• Strong communication skills with the ability to explain AI-related data requirements to non-technical stakeholders
• Experience validating AI-, ML-, or LLM-based solutions is considered a strong advantage

• Language Skills: Fluent English skills are required. German language skills are beneficial.
• Personality:

• Strong analytical mindset combined with sound business understanding
• Structured, pragmatic, and solution-oriented working style
• Strong communication and collaboration skills
• Ability to influence and align stakeholders without formal authority
• Comfortable working in dynamic and evolving environments
• Strong prioritization skills and the ability to turn complexity into