Biotech Health Data Governance Lead

What if your expertise in biotech data governance could directly shape how AI understands and works with life sciences research? We're looking for a Biotech Health Data Governance Lead to ensure that clinical trial and research data is accurate, traceable, compliant, and ready to power the next generation of AI-driven scientific discovery.

This is a fully remote, flexible contract role built for experienced professionals who know how to navigate the complex intersection of data integrity, regulatory compliance, and scientific research.

• Organization:
  Alignerr
• Type:
  Hourly Contract
• Location:
  
  Remote
• Commitment: 10-40 hours/week

• Lead governance of biotech research and clinical trial data - ensuring accuracy, lineage, and auditability for scientific analysis and regulatory submissions.
• Define and enforce data policies for classification, access, security, and metadata across research, clinical, regulatory, and partner teams.
• Enable secure, governed data access for analytics, innovation, and external collaborations while protecting confidential and patient-related information.
• Collaborate with scientific, IT, compliance, and business stakeholders to align data standards, workflows, and best practices.
• Support the development of high-quality, trustworthy data pipelines that underpin cutting-edge AI model training in life sciences.

• Experienced in leading or implementing data governance programs within biotech, life sciences, clinical research, or other regulated data environments.
• Deep understanding of data privacy, security, compliance frameworks, and regulatory expectations for research and clinical trial data.
• Skilled at bridging scientific, technical, and business teams - translating complex data requirements into practical, enforceable policies.
• Naturally detail-oriented with a systematic approach to data quality, traceability, and auditability.
• Self-directed and comfortable working independently in a remote, asynchronous environment.

• Prior experience with data annotation, data quality evaluation, or AI training workflows.
• Familiarity with regulatory submission standards such as FDA, EMA, or ICH guidelines.
• Background in clinical data management, biostatistics, or research informatics.
• Exposure to AI/ML data pipelines or life sciences technology platforms.

• Work on cutting-edge AI projects alongside leading research labs and life sciences organizations.
• Fully remote and flexible - work when and where it suits you.
• Freelance autonomy with the structure of meaningful, high-impact work.
• Make a direct contribution to AI systems that advance scientific discovery and improve human health.
• Potential for ongoing work and contract extension as new projects launch.