About the Role
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
What You'll Do
- 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
Who You Are
- 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
Nice to Have
- 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
Why Join Us
- 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