Biotech Health Data Governance Lead
Indexed description
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 submissions, and advanced AI-driven analytics. This is a fully remote, flexible contract role built for experienced life sciences and clinical data professionals who want meaningful, high-impact work on their own terms.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 10–40 hours/week
- 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 standards, and metadata management 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 data quality gaps and lead initiatives to remediate issues across research and clinical data pipelines
- Collaborate with scientific, IT, compliance, and business stakeholders to align data standards, workflows, and governance frameworks
- Support AI model development by ensuring the underlying biotech and clinical datasets meet rigorous quality and compliance standards
- Experienced in leading or implementing data governance programs within biotech, life sciences, clinical research, or other regulated data environments
- Deep understanding of data privacy, security, compliance frameworks, and regulatory expectations for research and clinical trial data (e.g., FDA, ICH, GCP)
- Skilled at navigating cross-functional teams — bridging the gap between scientists, IT professionals, compliance officers, and business stakeholders
- Detail-oriented and systematic, with a strong instinct for data quality and auditability
- Comfortable working independently and asynchronously in a remote, flexible environment
- Prior experience with data annotation, data quality evaluation, or AI training data pipelines
- Familiarity with clinical data management systems, EDC platforms, or research data repositories
- Background in regulatory affairs, clinical operations, or translational research
- Exposure to AI or machine learning workflows in a life sciences context
- Work at the intersection of cutting-edge AI and life sciences research — a genuinely rare opportunity
- Fully remote and flexible — structure your hours around your life, not the other way around
- Freelance autonomy with the substance of high-stakes, meaningful work
- Contribute directly to AI initiatives that support better science and faster discovery
- Potential for ongoing work and contract extension as new projects launch
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