The Clinical Data Engineer serves as an expert in USDM, driving digital protocol generation and enabling seamless data flow across the clinical development lifecycle, while collaborating across functions to optimize processes and ensure compliance with industry standards.
Serves as a subject matter expert in the implementation, application, and advancement of USDM standards to enable digital protocol generation and streamlined digital data flow across the clinical development lifecycle. This role provides strategic and technical leadership in translating protocol concepts into structured, standards-driven digital artifacts, ensuring alignment with industry data standards and regulatory expectations.
ResponsibilitiesUSDM Strategy & Implementation
- Serve as the organizational expert on Unified Study Definition Model (USDM) standards and their practical implementation.
- Lead the adoption and operationalization of USDM for digital protocol authoring and downstream data reuse.
- Interpret and apply USDM standards to enable structured protocol development and digital study definitions.
- Ensure alignment of study design metadata with industry standards (e.g., CDISC, regulatory frameworks).
Digital Protocol Generation
- Drive the implementation of USDM-based digital protocol generation processes.
- Translate narrative protocol content into structured, machine-readable representations.
- Support the integration of digital protocol components into downstream systems (e.g., EDC, CTMS, regulatory submissions, analytics platforms).
- Provide expertise on metadata-driven workflows and automation opportunities.
Digital Data Flow (DDF) Enablement
- Demonstrate a strong understanding of the Digital Data Flow (DDF) concept and its application across the clinical development lifecycle.
- Map upstream study definitions to downstream operational and data collection systems.
- Identify opportunities to eliminate redundant data entry and enable seamless data reuse.
- Collaborate with technology teams to design interoperable workflows supporting end-to-end data traceability.
Biomedical Concept Modeling
- Apply biomedical domain knowledge to ensure accurate representation of study objectives, endpoints, procedures, and assessments within structured data models.
- Ensure consistent modeling of biomedical concepts within USDM frameworks.
- Collaborate with clinical and scientific stakeholders to validate digital representations of study design.
- Promote standardization of biomedical terminology and alignment with controlled vocabularies.
Cross-Functional Collaboration & Consulting
- Act as a consultant to study teams on best practices for structured protocol design and standards implementation.
- Partner with Clinical Development, Data Management, Biostatistics, Regulatory Affairs, and IT to align digital strategy.
- Represent the organization in industry working groups or standards forums as appropriate.
- Provide training and knowledge-sharing sessions on USDM and Digital Data Flow concepts.
Process Optimization & Innovation
- Identify gaps in current protocol authoring and data flow processes and recommend innovative solutions.
- Support the development of internal standards, governance frameworks, and SOPs related to digital protocol generation.
- Stay current with evolving USDM standards, CDISC updates, and regulatory guidance.
- Contribute to digital transformation initiatives across clinical development.
Education
Bachelor’s degree in Life Sciences, Biomedical Sciences, Health Informatics, Computer Science, or related discipline required. Advanced degree preferred.
Experience
- Demonstrated expertise in Unified Study Definition Model (USDM) standards.
- Strong understanding of Digital Data Flow (DDF) concepts and implementation.
- Experience with digital protocol generation or structured protocol authoring platforms.
- Deep understanding of biomedical concepts within clinical research.
- Experience with industry standards such as CDISC (SDTM, ADaM, CDASH), regulatory frameworks, and metadata-driven systems.
- Experience in clinical development, data management, or clinical systems implementation preferred.
Skills & Competencies
- Strong analytical and systems-thinking capabilities.
- Ability to translate complex scientific and technical concepts into structured data models.
- Excellent communication and stakeholder engagement skills.
- Strategic mindset with the ability to drive innovation and change.
- Strong documentation and standards governance experience.
Top Skills
Cdisc
Ctms
Edc
Metadata-Driven Systems
Unified Study Definition Model (Usdm)
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