Precision Medicine Data Lead

Alignerr; Atlanta (GA); Remote; USD 110,000 - 165,000; Part time

Job summary

Alignerr is seeking a Precision Medicine Data Lead (AI Training) to design and oversee data pipelines that merge genomics, clinical records, biomarkers, and healthcare data into unified analytics platforms. You will drive analytics strategies for AI-driven clinical research and collaborate with clinicians, researchers, and engineers to ensure data quality and regulatory compliance.

You will guide data governance and integration efforts, translate complex data into actionable insights for

Qualifications

• Experience in healthcare data analytics and governance.
• Ability to translate complex data into actionable insights for clinical/scientific audiences.
• Proven track record leading cross-functional teams in regulated environments.

Responsibilities

• Design and oversee data pipelines integrating genomics, clinical records, biomarkers, and healthcare data.
• Lead analytics strategies to turn integrated data into research insights for AI-driven studies.
• Ensure data quality, regulatory compliance, and alignment with project goals.
• Communicate findings to scientific and non-technical stakeholders.
• Apply domain expertise to improve AI systems understanding of healthcare data.

Skills

Healthcare analytics

Data governance

Data integration

Leadership

Regulatory compliance

Cross-functional teamwork

Tools

EHR data systems

Cloud analytics platforms

Job description

Precision Medicine Data Lead (AI Training)

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? We're looking for a Precision Medicine Data Lead to guide how complex healthcare datasets are integrated, governed, and transformed into insights that power the next generation of AI-driven clinical research.

This is a fully remote, flexible contract role built for experienced professionals in healthcare data, genomics, or life sciences analytics who want to work at the cutting edge of AI and precision medicine.

• Organization: Alignerr
• Type: Hourly Contract
• Location: Remote
• Commitment: 10-40 hours/week

What You'll Do

• Design, oversee, and optimize pipelines that integrate genomics, clinical records, biomarkers, and healthcare data into unified analytics platforms
• Lead analytical strategies that convert complex, integrated datasets into actionable insights for research, clinical decision support, and precision medicine initiatives
• Collaborate with clinicians, researchers, and technical teams to ensure data quality, regulatory compliance, and strategic alignment
• Communicate findings and data strategies clearly to both scientific and non-technical stakeholders
• Apply your domain expertise to help AI systems better understand and reason about healthcare and genomic data

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 clinical or scientific audiences
• Skilled at working cross-functionally with clinical, research, and engineering teams in regulated or highly technical environments
• Detail-oriented, methodical, and confident making high-stakes data decisions
• Self-motivated and reliable when working independently in a remote setting

Nice to Have

• Prior experience with data annotation, data quality, or evaluation systems
• Familiarity with AI or machine learning workflows applied to healthcare or life sciences
• Background in bioinformatics, clinical informatics, or translational research
• Experience with cloud-based analytics platforms or EHR data systems

Why Join Us

• Work on cutting-edge AI projects alongside leading research labs and AI teams
• Fully remote and flexible - work when and where it suits you
• Freelance autonomy with the structure of meaningful, high-impact work
• Contribute directly to AI that could transform how personalized medicine is practiced at scale
• Exposure to advanced large language models and how they're trained on complex scientific domains
• Potential for ongoing work and contract extension as new projects launch