About the Role
Biotech Health Data Governance Lead (AI Training)
About The Role
What if your expertise in biotech and clinical data could directly shape how AI understands and operates within one of the most consequential fields in science? 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, clinical research, or regulated data environments who want to make a real impact at the intersection of biotech and AI.
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 full auditability for scientific analysis and regulatory submissions
Define and enforce data policies covering classification, access controls, security, and metadata standards across research, clinical, regulatory, and partner teams
Enable secure, governed data access for analytics, innovation, and external collaborations — while rigorously protecting confidential and patient-related information
Collaborate with scientific, IT, compliance, and business stakeholders to align data standards and workflows across complex, multi-team environments
Support AI training initiatives with high-quality, well-governed life sciences data that meets the standards required by leading research organizations
Who You Are
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 frameworks, and regulatory expectations specific to research and clinical trial data
A natural collaborator who can bridge scientific, technical, and business teams around shared data standards
Detail-oriented and systematic — you understand that in regulated environments, data quality isn't optional
Self-motivated and comfortable working independently in a remote, asynchronous setting
Nice to Have
Prior experience with data annotation, data quality evaluation, or AI training datasets
Familiarity with regulatory frameworks such as FDA 21 CFR Part 11, GCP, HIPAA, or GDPR as applied to clinical and research data
Background in bioinformatics, clinical data management, or health informatics
Experience working with external research partners or cross-functional life sciences teams
Why Join Us
Work at the frontier of AI and life sciences with teams building the next generation of research-grade AI models
Fully remote and flexible — structure your work around your schedule
Freelance autonomy with the substance of meaningful, high-impact technical work
Gain exposure to how cutting-edge AI systems are trained and validated using real scientific data
Potential for ongoing work and contract extension as new projects launch
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