About the Role
What if your expertise in genomics and clinical data could directly shape how AI understands and advances personalized medicine for millions of patients worldwide? We're looking for a Precision Medicine Data Lead to guide the integration, governance, and analysis of complex healthcare datasets — helping build AI systems that power the next generation of clinical decision-making.
This is a fully remote, flexible contract role designed for experienced professionals in healthcare data, genomics, or life sciences who want to apply their expertise to cutting-edge AI development.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 10–40 hours/week
What You'll Do
- Design, oversee, and optimize data pipelines that integrate genomics, clinical records, biomarkers, and other healthcare datasets into unified analytics platforms
- Lead analytical strategies that transform complex, integrated datasets into actionable insights for clinical research, decision support, and precision medicine initiatives
- Evaluate and validate how AI systems reason over healthcare and genomic data — identifying gaps, errors, and opportunities for improvement
- Collaborate with clinicians, researchers, and technical teams to ensure data quality, regulatory alignment, and scientific rigor
- Communicate findings and strategic recommendations clearly to both technical and non-technical stakeholders
- Contribute to data annotation, quality evaluation, and structured feedback workflows that improve AI model performance in healthcare contexts
Who You Are
- Experienced working with large-scale healthcare, genomic, or life sciences datasets in analytics or data leadership roles
- Strong background in data integration, data governance, and translating complex data into meaningful insights for scientific or clinical audiences
- Comfortable working cross-functionally with clinical, research, and engineering teams in regulated or highly technical environments
- Naturally detail-oriented with a rigorous, systematic approach to data quality and validation
- Self-directed and effective when working independently in asynchronous, remote settings
Nice to Have
- Prior experience with data annotation, data quality systems, or AI model evaluation
- Familiarity with bioinformatics tools, EHR systems, or clinical data standards (HL7, FHIR, etc.)
- Background in translational research, clinical informatics, or precision oncology
- Exposure to machine learning workflows applied to healthcare or life sciences data
Why Join Us
- Work alongside world-leading AI research labs on projects at the frontier of healthcare AI
- Fully remote and flexible — structure your work around your life, not the other way around
- Freelance autonomy with the substance of meaningful, high-impact work
- Direct exposure to how advanced large language models are trained and evaluated in specialized scientific domains
- Potential for ongoing work and contract extension as new projects launch