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Stanford University’s Division of Computational Medicine seeks a Research Data Analyst 2 to help reveal how rare diseases emerge in patients’ medical histories. You will work with electronic health records from Stanford patients with confirmed diagnoses to identify cohorts and reconstruct diagnostic journeys across ten rare diseases.
You will write Python and SQL, build tools, and collaborate with faculty, clinicians, and researchers.
Stanford’s Division of Computational Medicine brings together expertise in biomedical informatics, data science, and medicine to tackle complex questions about human health. We develop computational and statistical methods that help researchers make sense of health data and generate evidence for clinical and translational research.
We are seeking a Research Data Analyst 2 to help reveal how rare diseases emerge in patients’ medical histories. Working with electronic health records from Stanford patients with confirmed diagnoses, you will develop methods to identify patient cohorts and reconstruct diagnostic journeys across 10 rare diseases. Your work will connect information from clinical notes, diagnoses, procedures, medications, and laboratory results to support research on disease recognition and risk modeling.
In this role, you will contribute throughout the research process, from translating clinical questions into computational methods to evaluating results and sharing findings in publications and presentations. You will write Python and SQL code, build tools that bring clinical expertise into method development, and work closely with faculty, clinicians, and technical researchers. This is an opportunity to apply your programming and analytical skills to clinically meaningful questions while deepening your experience in biomedical data science.
This position offers a hybrid schedule, with onsite work three days per week, subject to operational needs.
Bachelor's degree and three years of relevant experience orcombination of education and relevant experience.
Experience in a quantitative discipline such as economics, finance,statistics or engineering.