Senior R&D Data Architect & Modeling Leader

Osprey Life Sciences

Cambridge (MA)

On-site

USD 150,000 - 210,000

Full time

13 days ago

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Job summary

Osprey Life Sciences is seeking a Senior R&D Data Modeler / Data Architect to lead hands-on data modeling and architecture for a global biopharma client from Cambridge, MA. The role combines design of conceptual/logical/physical models, mappings, and harmonization with technical leadership of contractors, enabling AI-ready data foundations for Research, Clinical Operations, and analytics.

Ideal candidates have pharma or life sciences experience and a proven ability to drive data standards across

Qualifications

Deep, hands-on experience in data modeling, data architecture, and data harmonization.
Experience developing conceptual, logical, and physical data models and mapping specifications.
Experience integrating and harmonizing data across complex systems and data environments.
Strong understanding of data quality, metadata, master/reference data, governance, and data lifecycle principles.
Experience with cloud-based data platforms, data lakes, data hubs, and modern analytics environments.
Pharmaceutical, biotechnology, or life sciences experience, preferably within R&D.
Experience with Research and/or Clinical data; experience across both is strongly preferred.
Ability to operate as a hands-on player-coach and influence technical and business teams without direct authority.
Strong communication and stakeholder-management skills.

Responsibilities

Design and maintain conceptual, logical, and physical data models across R&D.
Develop source-to-target mappings, harmonization specifications, and data curation designs.
Establish and apply R&D data modeling standards and best practices.
Harmonize scientific, clinical, and operational data across multiple systems and sources.
Translate scientific and business requirements into scalable data structures and technical specifications.
Partner with Data Governance, Data Strategy, ontology, engineering, analytics, and R&D stakeholders to improve data quality, consistency, and accessibility.
Support common data models within Research and aggregated Clinical Operations models supporting reporting and analytics.
Design curated data assets that provide a foundation for advanced analytics, knowledge graphs, AI, and machine learning.
Provide technical leadership to contractor and offshore resources while remaining personally accountable for key modeling deliverables.
Collaborate with enterprise data teams while maintaining the specific data architecture needs of R&D.