Biotech Health Data Governance Lead

What if your deep knowledge of biotech data and regulatory compliance 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, and trustworthy — supporting cutting-edge AI development at the intersection of science and technology.

This is a fully remote, flexible contract role built for experienced professionals in biotech, life sciences, or regulated data environments who want to make a meaningful contribution to the future of AI-powered research.

• 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, security, and metadata across research, clinical, regulatory, and partner teams
• Enable secure, governed access to data for analytics, innovation, and external collaborations while protecting confidential and patient-related information
• Evaluate and improve data quality standards in ways that directly support AI model development in life sciences contexts
• Collaborate with scientific, IT, compliance, and business stakeholders to align data standards and workflows across functions

• Experienced in leading or implementing data governance programs within biotech, life sciences, clinical research, or regulated data environments
• Deeply familiar with data privacy, security, compliance frameworks, and regulatory expectations for research and clinical trial data
• Skilled at bridging scientific, technical, and compliance teams — translating complex data requirements into clear, actionable policies
• Detail-oriented and systematic — you understand that in regulated environments, the integrity of every data point matters
• Self-motivated and comfortable working independently in a remote, asynchronous setting

• Prior experience with data annotation, data quality frameworks, or AI evaluation systems
• Familiarity with regulatory submissions processes (FDA, EMA, or equivalent)
• Background working with clinical data standards such as CDISC, HL7, or FHIR
• Exposure to AI or machine learning workflows in a life sciences context

• 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
• Contribute to AI development that has real consequences for how science is done and how lives are improved
• Exposure to advanced AI models and how high-quality, governed data enables better science
• Potential for ongoing work and contract extension as new projects launch