Rare-Disease EHR Data Analyst — Biomedical Insights

Stanfordlivetickets; Palo Alto (CA); Hybrid; USD 110,000 - 140,000; Full time

Job summary

Stanford’s Division of Computational Medicine is seeking a Research Data Analyst 2 to reveal how rare diseases emerge in patients’ medical histories. You will work with Stanford patients’ EHR data to identify cohorts and reconstruct diagnostic journeys across multiple diseases, linking clinical notes, diagnoses, procedures, medications, and lab results to support disease recognition and risk modeling.

You will write Python and SQL code, build clinical-expertise tools, and collaborate with

Responsibilities

• Develop and evaluate methods to identify rare-disease cohorts using structured EHR data and clinical text.
• Build reproducible pipelines that organize clinical events into patient diagnostic timelines.
• Create annotation and review tools that help clinicians validate extracted information and guide improvements.
• Investigate data-quality issues and extraction errors, using clinical feedback to refine computational methods.
• Develop performance metrics and automated tests for timeline extraction and downstream disease-risk models.
• Translate analyses into clear datasets, figures, reports, presentations, and manuscript contributions.
• Document methods, validation results, and limitations so research findings can be understood and reproduced.
• Collaborate with clinical and technical colleagues to shape methods, interpret results, and advance the research.

Job description

Stanford’s Division of Computational Medicine is seeking a Research Data Analyst 2 to reveal how rare diseases emerge in patients’ medical histories. You will work with Stanford patients’ EHR data to identify cohorts and reconstruct diagnostic journeys across multiple diseases, linking clinical notes, diagnoses, procedures, medications, and lab results to support disease recognition and risk modeling.

You will write Python and SQL code, build clinical-expertise tools, and collaborate with