About the Role
What if your expertise in biotech data governance could directly shape how AI understands and works with clinical and life sciences data? 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 who know how to bring rigour and structure to complex data environments — without sacrificing speed or scientific progress.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 10–40 hours/week
What You'll Do
- Lead governance of biotech research and clinical trial data — ensuring accuracy, lineage, and full auditability for scientific analysis and regulatory submissions
- Define and enforce data policies covering classification, access controls, security protocols, and metadata standards across research, clinical, regulatory, and partner teams
- Enable secure, governed data access for analytics, innovation initiatives, and external collaborations — while protecting confidential and patient-related information
- Partner with scientific, IT, compliance, and business stakeholders to align data standards, resolve conflicts, and drive consistent workflows
- Identify and close gaps in data quality, documentation, and traceability across the data lifecycle
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 requirements, and regulatory expectations for clinical trial and research data
- A strong cross-functional collaborator — able to bridge the gap between scientific teams and technical or compliance stakeholders
- Methodical and detail-oriented with a track record of building governance frameworks that actually get adopted
- Comfortable working independently in a remote, asynchronous environment
Nice to Have
- Prior experience with data annotation, data quality evaluation, or AI training data pipelines
- Familiarity with regulatory frameworks such as FDA 21 CFR Part 11, ICH E6 GCP, or GDPR as applied to clinical data
- Exposure to clinical data management systems, EDC platforms, or research data repositories
- Experience designing metadata schemas or data dictionaries for scientific datasets
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 and purpose of meaningful, high-stakes work
- Contribute directly to AI initiatives that have real impact on scientific discovery and patient outcomes
- Gain exposure to how high-quality, governed data enables the next generation of AI in life sciences
- Potential for ongoing work and contract extension as new projects launch