Biomedical Data Scientist - AI-Driven Data Infrastructure

Abundance Network; United States; On-site; USD 80,000 - 110,000; Full time

Job summary

Stanford University is seeking a Research Data Analyst 2 - Biomedical Data Science to lead the development of research data infrastructure that harmonizes multimodal clinical research data across studies. You will apply data science, biomedical informatics, and AI methods to create standardized datasets for allergy and immunology research.

You will work with leading scientists and clinicians to accelerate discovery, drive translational research, and support high-quality published findings

Qualifications

• Bachelor's degree and at least three years of relevant experience.
• Experience in a quantitative discipline such as economics, finance, statistics or engineering.
• Strong writing and analytical skills; ability to prioritize workload.

Responsibilities

• Create complex charts and databases, perform statistical analyses, and prepare figures for publication.
• Design data collection instruments and analysis plans under supervision.
• Extract and harmonize data from notes, surveys, medical reports, and lab data, maintaining accuracy.
• Design and customize reports based on database content.
• Ensure regulatory compliance for data usage.
• Identify data quality issues and implement corrective actions.
• Provide documentation to investigators and research staff.
• Lead harmonization of multimodal data across studies to support secondary analyses and AI applications.

Skills

Excellent writing

Analytical skills

Prioritization

Education

Bachelor's degree

Tools

MS Office

Job description

Stanford University is seeking a Research Data Analyst 2 - Biomedical Data Science to lead the development of research data infrastructure that harmonizes multimodal clinical research data across studies. You will apply data science, biomedical informatics, and AI methods to create standardized datasets for allergy and immunology research.

You will work with leading scientists and clinicians to accelerate discovery, drive translational research, and support high-quality published findings