Biotech Health Data Governance Lead

Job summary

Govern biotech research and clinical trial data to ensure accuracy, lineage, and auditability for regulatory submissions. Define and enforce data policies and security standards while collaborating across scientific, IT, and compliance teams.

Job details

Biotech Health Data Governance Lead (AI Training) About The Role What if your deep expertise in biotech data governance could directly shape how AI understands and works with clinical and research data — influencing the next generation of life sciences discovery? 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 breakthroughs, regulatory filings, and advanced AI-driven analytics. This is a fully remote, flexible contract role built for experienced professionals who want autonomy, meaningful work, and the chance to sit at the intersection of life sciences and cutting-edge 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 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 Identify data quality issues and implement scalable processes to maintain integrity across complex, multi-team environments Serve as the connective tissue between scientific, IT, compliance, and business stakeholders to align data standards and workflows Who You Are Experienced in leading or implementing data governance programs within biotech, life sciences, clinical research, or other regulated data environments Strong command of data privacy, security, compliance, and regulatory expectations specific to research and clinical trial data Skilled at collaborating across diverse teams — scientists, engineers, compliance officers, and business partners — to drive alignment on data standards Detail-oriented and systematic, with a track record of building governance frameworks that actually stick Comfortable working independently in a remote, asynchronous environment 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, ICH E6, GDPR, or HIPAA in the context of clinical research data Background in data architecture, metadata management, or master data management within life sciences Exposure to AI or machine learning pipelines and how high-quality governed data enables better model outcomes Why Join Us Work at the frontier of AI and life sciences — your governance expertise directly enables better science and smarter AI Fully remote and flexible — structure your hours around your life, not the other way around Freelance autonomy with the substance of high-impact, domain-specific work Collaborate with world-class AI research teams and life sciences organizations on projects that matter Potential for ongoing work and contract extension as new projects launch

What you’ll do

Govern biotech research and clinical trial data to ensure accuracy, lineage, and auditability for regulatory submissions. Define and enforce data policies and security standards while collaborating across scientific, IT, and compliance teams.

Requirements

Requires extensive experience leading data governance programs within biotech or regulated life sciences environments. Must have a strong command of data privacy, security, and regulatory expectations specific to clinical research.

Listed skills

• Regulatory Compliance · Preferred
• Stakeholder Management · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Data Governance
• Clinical Trial Data Management
• Data Privacy
• Regulatory Compliance
• Metadata Management
• Data Lineage
• Auditability
• Stakeholder Management
• Data Quality Evaluation
• AI Training Datasets
• Data Architecture
• Master Data Management

Job areas

• Data & Analytics
• Science & Research
• Healthcare
• Technology
• Management & Leadership