Biomedical Data Scientist — AI for Multimodal Clinical Data

SLAC; Palo Alto (CA); On-site; USD 90,000 - 135,000; Full time

Benefits offered by this job

Tuition options

Workshops and onsite conferences

Work/life and family-friendly policies

Social responsibility and sustainable,

Vibrant university culture

Job summary

Stanford University is seeking a Research Data Analyst 2 - Biomedical Data Science to lead the development of research data infrastructure and harmonize multimodal clinical data across studies. The successful candidate will apply modern data science, biomedical informatics, and AI methods to create standardized, research-ready datasets that accelerate discovery in allergy and immunology, supporting translational research at the Sean N.

Parker Center.

Qualifications

• Experience analyzing large datasets in biomedical research.
• Ability to develop research data infrastructure and harmonize multimodal data across studies.
• Experience with data analysis, statistics, and AI methods.

Responsibilities

• Create complex charts and databases, perform statistical analyses, and develop graphs and tables for publication and presentation.
• Assist with design of data collection instruments and statistical analysis plans.
• Prioritize and extract data from notes, survey results, medical reports, and laboratory data, maintaining accuracy and completeness.
• Design and customize reports based on data in the database.
• Oversee and monitor regulatory compliance for data utilization.
• Identify data issues using system reports and analyses and implement corrections.
• Provide documentation based on audit and reporting criteria to investigators and staff.
• Lead efforts to harmonize clinical, laboratory, genomic, biospecimen, imaging, and patient-reported data across studies into standardized datasets.

Job description

Stanford University is seeking a Research Data Analyst 2 - Biomedical Data Science to lead the development of research data infrastructure and harmonize multimodal clinical data across studies. The successful candidate will apply modern data science, biomedical informatics, and AI methods to create standardized, research-ready datasets that accelerate discovery in allergy and immunology, supporting translational research at the Sean N.

Parker Center.