About the Role
What if your expertise in biotech data governance could directly shape how AI understands and operates within one of the most complex, high-stakes domains 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 the next generation of AI-driven scientific discovery and regulatory submissions.
This is a fully remote, flexible contract role built for experienced professionals in life sciences, clinical research, or regulated data environments who want to apply their expertise at the frontier of AI development.
- 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 across 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
- Identify and resolve data quality issues that could impact scientific integrity or compliance
- Collaborate with scientific, IT, compliance, and business stakeholders to align data standards and workflows
- Support AI training initiatives by ensuring high-quality, well-structured, and trustworthy data pipelines
Who You Are
- Experienced in leading or implementing data governance programs within biotech, life sciences, clinical research, or other regulated data environments
- Deeply familiar with data privacy, security, compliance, and regulatory expectations specific to research and clinical trial data (e.g., GCP, HIPAA, FDA 21 CFR Part 11)
- Able to bridge scientific, technical, and compliance perspectives — translating complex requirements into clear, actionable data standards
- Naturally detail-oriented with a systematic approach to data quality and auditability
- Self-directed and comfortable working independently in a remote, asynchronous environment
Nice to Have
- Prior experience with data annotation, data quality evaluation, or AI training workflows
- Familiarity with metadata management tools, data catalogs, or clinical data management systems
- Background in biostatistics, bioinformatics, or regulatory affairs
- Experience working with 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
- Gain direct exposure to how high-quality governed data enables breakthroughs in AI and life sciences
- Potential for ongoing work and contract extension as new projects launch