$121,600 – $194,500
Listed on Moderna’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
This role leads the definition and delivery of data products and AI solutions across Moderna's manufacturing and quality organization, translating operational challenges into governed, reusable data assets. It suits someone with pharmaceutical or regulated-industry experience who can bridge business and technical teams, write clear specifications, and ensure data solutions are production-ready and compliant.
Our summary, not Moderna’s wording. The full posting is on their site.
Skills this role names
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What they ask for
Required
- Bachelor's or Master's degree in Engineering, Computer Science, Life Sciences, Data Science, or related field
- 4+ years in pharmaceutical, biotech, or regulated industries with CMC exposure
- 6+ years defining and delivering data, analytics, reporting, or digital solutions in production workflows
- Familiarity with modern data concepts including data modeling, data quality, and cloud platforms
- Understanding of pharmaceutical systems and data domains (Veeva, SAP, MES, LIMS)
- Ability to translate business needs into clear, structured requirements for engineering teams
- Proven capability to write specifications and use case definitions as handoffs to builders
- Experience working across business and technical stakeholders to drive alignment
- Knowledge of data governance principles including ownership, classification, access control, and quality standards
- Understanding of GxP, data integrity, and compliance for data, analytics, and AI solutions
Nice to have
- Direct experience with Veeva Quality, LabVantage, Syncade, or similar MES and LIMS platforms
- Experience with dbt, Redshift, Snowflake, or similar data tools
- Knowledge of medallion data architecture patterns
- Familiarity with GitHub-based workflows, docs-as-code, or version-controlled specifications
- Track record of driving adoption of data products into sustained operational use
- Participation in or contribution to data governance programs
- Interest in or experience with agentic AI workflows and how data products can be consumed by AI agents
- Familiarity with AI/ML use case evaluation including RAG pipelines and LLM design
- Background in GxP validation for data systems and analytics platforms