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Research Data Analyst - Hematological Malignancies

Job in Palo Alto, Santa Clara County, California, 94306, USA
Listing for: Stanford University
Full Time position
Listed on 2026-08-22
Job specializations:
  • Science
    Clinical Research, Data Scientist
Salary/Wage Range or Industry Benchmark: 85000 - 120000 USD Yearly USD 85000.00 120000.00 YEAR
Job Description & How to Apply Below

The Division of Hematology is a progressive and dynamic center for basic and translational science, clinical research, patient care, and teaching, where clinicians, scholars, investigators, and trainees work together to harness the power and resources of Stanford Medicine in the pursuit of excellence.

Core Duties:
  • 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.
Minimum Education:

Bachelor's degree and three years of relevant experience or combination of education and relevant experience.

Minimum Experience:

Experience in a quantitative discipline such as economics, finance, statistics or engineering.

Knowledge, Skills and Abilities:
  • Substantial experience with MS Office and analytical programs.
  • Excellent writing and analytical skills.
  • Ability to prioritize workload.
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