Biotech Health Data Governance Lead (AI Training)
About The Role
What if your deep knowledge of biotech and clinical trial data could directly shape how the world's most advanced AI models understand life sciences We're looking for a Biotech Health Data Governance Lead to ensure that research and clinical data used in AI training is accurate, traceable, compliant, and ready to power scientific discovery and regulatory submissions.
This is a fully remote, flexible contract role built for experienced life sciences and data governance professionals who want meaningful, high-stakes work — on their own terms.
- 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 control, security, and metadata standards 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 complex, cross-functional environments
- Support the integrity and trustworthiness of data used to train and evaluate cutting-edge AI models in life sciences contexts
Who You Are
- Experienced in leading or implementing data governance programs in biotech, life sciences, clinical research, or other regulated data environments
- Strong understanding 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 scrutiny
- Self-directed and reliable when working independently in an asynchronous, remote 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, GCP, HIPAA, or GDPR in a life sciences context
- Background in clinical data management, biostatistics, or research informatics
- Exposure to AI/ML data workflows or working with data science teams
Why Join Us
- Work at the intersection of life sciences and cutting-edge AI with leading research organizations
- Fully remote and flexible — work when and where it suits you
- Freelance autonomy with the structure and purpose of high-impact, meaningful work
- Gain exposure to advanced AI models and the role that trustworthy data plays in better science
- Potential for ongoing work and contract extension as projects scale
