R&D Senior Product Owner Data Governance and Semantics
Pubblicato il 05-10-2026 - Chiesi in Piacenza
Overview As part of Chiesi’s R&D; transformation, you will lead the data governance and semantics effort to maximize R&D; data value. You will shape the semantic layer, metadata, and knowledge graph to enable trusted, discoverable data and AI-driven insights. You’ll collaborate with SMEs and IT to enforce governance and quality, driving a data-driven culture across R&D.; This role offers visibility across clinical and GICT domains and a meaningful impact on research productivity and compliance.
Retribuzione / Benefits
- annual premio scheme
- pension
- private medical insurance
- wellbeing programme
- flexible benefits programme
- remote working
Responsabilità
- Lead semantic layer, data model, and ontologies to unify the R&D; data ecosystem with a focus on clinical data domains
- Architect a knowledge graph integrating heterogeneous R&D; data
- Ensure linked metadata and machine-readable glossaries for advanced data discovery and AI insights
- Develop and implement a comprehensive R&D; data governance framework
- Define data stewardship policies, roles,
and quality rules in line with governance policies
- Collaborate with functional SMEs to ensure data is defined and maintained per guidelines
- Promote ALCOA+/FAIR principles across data management
- Define product requirements, backlog, and roadmap for data sets delivered by engineering
- Monitor data quality KPIs and usage metrics; iterate on enhancements
- Establish data quality frameworks with validation rules, profiling, and anomaly detection
- Engage stakeholders and communicate governance value; mentor and balance priorities
- Establish metrics to track governance effectiveness and drive continuous improvement
Requisiti fondamentali
- Advanced degree (Master’s/PhD) in Life Sciences, Data Science, or related field
- Minimum 5 years in R&D; clinical domain
- Minimum 3 years in a Product Owner or similar strategic role with backlog management
- Strong background in data modeling techniques
- Experience in Pharmaceutic