Biotech Health Data Governance Lead

What if your deep expertise in biotech data governance could directly shape how AI understands and works with clinical and research data at a global 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 discovery, regulatory filings, and advanced AI-driven analytics.

This is a fully remote, flexible contract role built for experienced professionals in life sciences and regulated data environments who want to do meaningful work on their own terms.

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

• Govern biotech research and clinical trial data to ensure accuracy, lineage, and auditability for scientific analysis and regulatory submissions
• Define and enforce data policies covering classification, access controls, security standards, and metadata management across research, clinical, regulatory, and partner teams
• Enable secure, governed data access for analytics, innovation pipelines, and external collaborations — while protecting confidential and patient-related information
• Identify gaps in existing data workflows and recommend practical, scalable governance improvements
• Collaborate across scientific, IT, compliance, and business stakeholders to align data standards and ensure consistent application of governance frameworks

• Experienced in leading or implementing data governance programs within biotech, life sciences, clinical research, or other regulated data environments
• Strong working knowledge of data privacy, security, compliance, and regulatory expectations for research and clinical trial data (e.g., GDPR, HIPAA, FDA 21 CFR Part 11)
• Comfortable navigating cross-functional teams — bridging the gap between scientists, engineers, compliance officers, and business stakeholders
• Detail-oriented and systematic, with a track record of building governance frameworks that hold up under regulatory scrutiny
• Self-directed and capable of delivering high-quality work independently in a remote, asynchronous environment

• Prior experience with data annotation, data quality assurance, or evaluation systems
• Familiarity with AI model training workflows and how high-quality structured data enables better model performance
• Exposure to clinical data management systems (CDMS), electronic data capture (EDC), or LIMS platforms
• Background in bioinformatics, regulatory affairs, or translational research

• Work at the intersection of cutting-edge AI research and life sciences — a rare and genuinely exciting opportunity
• 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 AI initiatives that improve how science is done and how clinical data is trusted
• Potential for ongoing engagement and contract extension as projects evolve