Remote Precision Medicine Data Lead for AI Training

Alignerr; Oxford; Remote; GBP 83,000 - 165,000; Part time

Job summary

Alignerr is seeking a Precision Medicine Data Lead to guide the integration of genomics and clinical data into analytics platforms and to help train AI models for precision medicine. This is a fully remote, hourly contract role with 10–40 hours per week, collaborating with clinicians and researchers to influence AI-driven healthcare decisions.

You will design data pipelines, ensure data quality and regulatory alignment, and translate complex datasets into actionable insights for AI training and

Qualifications

• Experience with large-scale healthcare/genomics datasets in analytics or data leadership.
• Strong data integration and governance background.
• Experience working in regulated or highly technical environments.

Responsibilities

• Design, oversee, and optimize data pipelines integrating genomics, clinical records, and biomarkers into analytics platforms.
• Lead analytical strategies to transform datasets into actionable insights for precision medicine research and clinical decision support.
• Collaborate with clinicians, researchers, and technical teams to ensure data quality, regulatory alignment, and strategic coherence.
• Communicate findings clearly to scientific and non-technical stakeholders.
• Help shape AI models by guiding data to improve training for healthcare applications.

Skills

Healthcare data analytics

Genomics data integration

Data governance

Cross-functional collaboration

Education

Advanced degree in bioinformatics, data science, or life sciences

Job description

Alignerr is seeking a Precision Medicine Data Lead to guide the integration of genomics and clinical data into analytics platforms and to help train AI models for precision medicine. This is a fully remote, hourly contract role with 10–40 hours per week, collaborating with clinicians and researchers to influence AI-driven healthcare decisions.

You will design data pipelines, ensure data quality and regulatory alignment, and translate complex datasets into actionable insights for AI training and