Biotech Health Data Governance Lead

Job summary

Govern biotech research and clinical trial data to ensure accuracy, lineage, and auditability for regulatory submissions. Define and enforce data policies and quality standards to support AI model training and cross-functional scientific workflows.

Job details

Biotech Health Data Governance Lead (AI Training) About The Role What if your expertise in biotech data governance could directly shape how AI understands and works with clinical and research data — accelerating scientific discovery and improving how life sciences organizations operate at scale? We're looking for a Biotech Health Data Governance Lead to ensure that research and clinical trial data is accurate, traceable, compliant, and ready to power scientific breakthroughs, regulatory filings, and advanced AI-driven analytics. This is a fully remote, flexible contract role built for experienced professionals who understand the stakes of data integrity in regulated life sciences environments. Organization: Alignerr Type: Hourly Contract Location: Remote Commitment: 10–40 hours/week What You'll Do Govern biotech research and clinical trial data to ensure accuracy, lineage, and full auditability for scientific analysis and regulatory submissions Define and enforce data policies covering classification, access controls, security, and metadata across research, clinical, regulatory, and partner teams Enable secure, governed data access that supports analytics, innovation, and external collaboration — while protecting confidential and patient-related information Assess and document data quality standards to support AI model training and evaluation workflows Collaborate with cross-functional stakeholders — scientific, IT, compliance, and business teams — to align data standards and operational workflows Who You Are Experienced in leading or implementing data governance programs within biotech, life sciences, clinical research, or other regulated data environments Deeply familiar with data privacy, security, compliance, and regulatory expectations for research and clinical trial data A natural collaborator who can bridge scientific rigor with practical policy implementation across diverse teams Detail-oriented and systematic — you understand that in life sciences, data quality isn't a nice-to-have, it's a requirement Comfortable working independently in a remote, asynchronous environment Nice to Have Prior experience with data annotation, data quality evaluation, or AI training data pipelines Familiarity with frameworks such as FAIR data principles, CDISC standards, or GxP compliance requirements Background in regulatory affairs, clinical data management, or bioinformatics Experience working with AI or machine learning teams on data readiness and governance Why Join Us Work on cutting-edge AI and life sciences projects alongside leading research organizations Fully remote and flexible — structure your work around your life, not the other way around Freelance autonomy with the substance of meaningful, high-impact work Contribute directly to the data infrastructure that enables better science and smarter AI Exposure to advanced AI models and how high-quality governed data drives better outcomes in research and discovery Potential for ongoing work and contract extension as new projects launch

What you’ll do

Govern biotech research and clinical trial data to ensure accuracy, lineage, and auditability for regulatory submissions. Define and enforce data policies and quality standards to support AI model training and cross-functional scientific workflows.

Requirements

Requires extensive experience leading data governance programs within biotech or regulated life sciences environments. Candidates must be deeply familiar with data privacy, security, and regulatory expectations for clinical research data.

Benefits

• Flexible schedule • Freelance autonomy • Exposure to advanced AI models

Listed skills

• Regulatory Compliance · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Data Governance
• Clinical Trial Data Management
• Data Privacy
• Regulatory Compliance
• Data Lineage
• Metadata Management
• AI Training Data Pipelines
• Data Quality Evaluation
• FAIR Data Principles
• CDISC Standards
• GxP Compliance
• Bioinformatics
• Data Annotation
• Stakeholder Collaboration
• Auditability
• Access Control

Job areas

• Data & Analytics
• Science & Research
• Healthcare
• Technology
• Management & Leadership