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Stanford University in California seeks a Research Data Analyst 2 to manage and analyze large, technical data in the Department of Biomedical Data Science. The role involves creating datasets, importing/exporting data, performing statistical analyses, and preparing reports for publication.
You will prioritize data extraction from diverse sources, develop complex charts and tables, ensure regulatory compliance, and support investigators with statistics or surveys.
Stanford University is seeking a Research Data Analyst 2 to manage and analyze large amounts of information, typically technical or scientific in nature, independently with minimal supervision in the Department of Biomedical Data Science.
Manage and analyze large amounts of information, which is typically technical or scientific in nature including creating large and complex data sets, abstracting and formatting data, importing and exporting data between files, performing statistical analysis, and preparing reports and manuscripts for publication.
Prioritize and extract data from a variety of sources such as notes, survey results, medical reports, and laboratory data, and maintain its accuracy and completeness.
Determine additional data collection and reporting requirements.
Design and customize reports based upon data in the database. Oversee and monitor regulatory compliance for utilization of the data.
Use system reports and analyses to identify potentially problematic data, make corrections, and eliminate root cause for data problems or justify solutions to be implemented by others.
Create complex charts and databases, perform statistical analyses, and develop graphs and tables for publication and presentation.
Serve as a resource for non-routine inquiries such as requests for statistics or surveys.
Test prototype software and participate in approval and release process for new software.
Provide documentation based on audit and reporting criteria to investigators and research staff.
Bachelor's degree and three years of relevant experience or combination of education and relevant experience.
Experience in a quantitative discipline such as economics, finance, statistics or engineering.
Substantial experience with MS Office and analytical programs.
Excellent writing and analytical skills.
Ability to prioritize workload.