Biotech Health Data Governance Lead

Biotech Health Data Governance Lead (AI Training)
About The Role
What if your expertise in biotech and clinical 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 research and clinical trial data is accurate, traceable, compliant, and ready to power scientific discovery, regulatory filings, and next-generation AI models.
This is a fully remote, flexible contract role built for experienced professionals in biotech, life sciences, or regulated data environments. If you've built or led governance programs that keep complex research data trustworthy and audit-ready, we want to hear from you.
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 controls, 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
Collaborate with scientific, IT, compliance, and business stakeholders to align data standards and workflows across the organization
Support the development of high-quality, trustworthy datasets that underpin cutting-edge AI models in life sciences
Who You Are
Experienced in leading or implementing data governance programs in biotech, life sciences, clinical research, or regulated data environments
Strong working knowledge of data privacy, security, compliance frameworks, and regulatory expectations for research and clinical trial data
A natural collaborator — comfortable bridging scientific, technical, compliance, and business teams to align on data standards
Detail-oriented and systematic, with a track record of building governance structures that hold up under regulatory scrutiny
Self-motivated and reliable when working independently in a remote, async environment
Nice to Have
Prior experience with data annotation, data quality assessment, or AI evaluation systems
Familiarity with clinical data standards such as CDISC, FHIR, or HL7
Background in regulatory submissions or GxP-compliant environments
Experience working across cross-functional or globally distributed teams
Why Join Us
Work on cutting-edge AI projects alongside leading life sciences research teams and AI labs
Fully remote and flexible — work when and where it suits you
Freelance autonomy with the structure of meaningful, high-impact work
Play a direct role in ensuring the data quality that drives better science and smarter AI
Potential for ongoing work and contract extension as new projects launch

Work arrangement
No