Data Modeling Expert: FAIR Data for AI-Driven R&D

F. Hoffmann-La Roche AG; United Kingdom; Remote; GBP 90,000 - 115,000; Full time

Job summary

Roche is forming a Computational Sciences Center of Excellence and seeks a Data Modeling Expert to advance data modeling, semantics, ontologies and standards. Based onsite at Welwyn, you will enable FAIR, high-quality data for researchers and AI tools across REDs.

You will translate scientific requirements into data models, influence data governance strategies and support data readiness for AI/ML initiatives within a matrixed organization.

Qualifications

• Master's degree or higher in a scientific or technical field.
• Experience in Data Governance, Data Standards, Data Modeling, Ontology Development or related fields.
• Ability to lead initiatives in a matrixed organization.

Responsibilities

• Act as a key subject matter expert on data modeling, ontologies, semantics, and standards efforts, interfacing closely with business/scientific stakeholders and informatics/engineering colleagues.
• Translate complex scientific requirements from various parts of R&D into clear draft data models that can be leveraged by the wider FAIR data modeling team.
• Independently contribute to and, on occasion, drive the development of data models and standards and/or information architecture solutions.
• Independently contribute to and, on occasion, drive strategies that ensure pan-RED Roche data is ready for AI/ML (AI data readiness).
• Foster a OneRoche data-centric mindset within the team, advocating for data standards, governance, and FAIR principles.

Skills

Data governance

Data standards

Data modeling

Ontology development

Communication skills

Education

Master's degree or higher in a scientific or technical field

Job description

Roche is forming a Computational Sciences Center of Excellence and seeks a Data Modeling Expert to advance data modeling, semantics, ontologies and standards. Based onsite at Welwyn, you will enable FAIR, high-quality data for researchers and AI tools across REDs.

You will translate scientific requirements into data models, influence data governance strategies and support data readiness for AI/ML initiatives within a matrixed organization.