Start Date: 1 July 2025
End Date: 31 December 2025
Location: Remote
Language Requirement: English (mandatory), German (preffered)
Engagement Type: Contract
Role Overview We are seeking an experienced Data & AI Consultant with a strong background in pharmaceutical manufacturing. The focus of this role is on consulting with existing pharma clients on how to structure, manage, and leverage data generated in manufacturing environments.
The ideal candidate is not just technically capable, but also highly effective in consulting settings—able to understand complex pharma manufacturing contexts, translate business needs into data strategies, and guide delivery teams from concept to execution.
Key Responsibilities
- Advise pharmaceutical clients on data architecture and strategy specific to manufacturing processes and systems.
- Lead consulting engagements focused on the design and implementation of data platforms, data governance models, and AI/analytics solutions in pharma manufacturing.
- Collaborate with Internal delivery teams (data engineering, AI, domain experts) to ensure high-impact, compliant outcomes.
- Engage in pre-sales and proposal development, shaping data & AI offerings for the Health Market Unit.
- Guide clients on topics such as data compliance (e.g., GxP, 21 CFR Part 11), data lifecycle management, and readiness for AI initiatives.
- Contribute internally to capability development and act as a thought partner for the broader Data & AI consulting team.
- Minimum 5 years of experience in data consulting roles with direct involvement in pharma manufacturing projects.
- In-depth understanding of manufacturing data structures and systems, including MES, LIMS, SCADA, batch records, and related data sources.
- Experience working in regulated environments with knowledge of compliance requirements (e.g., GxP, electronic records).
- Proven ability to lead engagements from strategy through delivery in a client-facing consulting role.
- Strong communication and stakeholder management skills, with the ability to work across technical and business teams.
- Fluency in English (written and verbal).
- Background in data engineering or data science applied in a manufacturing context.
- Familiarity with modern data platforms (e.g., Azure, Snowflake, Databricks).
- Experience with AI use cases in manufacturing such as predictive maintenance, process optimization, or anomaly detection.
- German language skills (optional but beneficial).