Data Scientist

Data Scientist . The Stankovic Laboratory at Stanford University School of Medicine seeks a highly motivated research scholar with expertise in data science, epidemiology, and computational analysis of large-scale electronic health record (EHR) data. The individual will join a dynamic, interdisciplinary team in the Stanford Department of Otolaryngology–Head & Neck Surgery, with access to the university’s rich ecosystem of data science, epidemiology, and computational health resources. Mentorship will emphasize both technical skill development and career advancement. Opportunities for co-authorship, conference presentations, and cross-disciplinary collaborations are abundant.

Responsibilities:

• Develop reproducible code in Python and/or R for data wrangling, analysis, and visualization.
• Extract, manage, and analyze large-scale EHR data within secure data environments (e.g., N3C Enclave and Cosmos).
• Implement epidemiologic study designs (e.g., retrospective cohort, target trial emulation, propensity-score matching).
• Conduct and interpret statistical analyses, including regression, survival, and longitudinal models.
• Collaborate on manuscript writing, figure preparation, and presentation of findings for ongoing projects in the lab.
• Contribute to grant proposals and new analytic frameworks.
• Engage in interdisciplinary collaboration with hearing and balance researchers, physicians, and epidemiologists.

Qualifications:

Required :

• Master’s or PhD degree in a quantitative or biomedical field such as Epidemiology, Biostatistics, Data Science, Computer Science, Biomedical Informatics, or related discipline. A Bachelor’s degree plus 3 years of relevant experience will also be considered.
• Strong proficiency in Python and/or R for data analysis and statistical modeling.
• Experience with EHR, large-scale health data (OMOP, PCORnet, or similar), or real-world databases (e.g., Optum, IQVIA, Merative, Medicare/Medicaid, etc.)
• Understanding of epidemiologic study design, bias, and confounding.
• Excellent written and verbal communication skills, with proficiency in English
• Commitment to reproducible and transparent research practices.
• Interest in collaborative science.

Preferred :

• Experience working with Spark/PySpark, SQL, or cloud-based analytic environments.
• Familiarity with propensity-score matching, survival analysis, or causal inference methods.
• Prior exposure to biomedical or neuroscience applications (hearing or sensory research not required).

To Apply:

Please send the following materials in a single PDF to Rachel McGowan ([email protected]) and Dr. Shelley Batts ( [email protected] ) with the subject line Application – Data Scientist :

1. Cover letter describing your background, programming experience, and research interests.
2. Curriculum vitae.
3. Contact information for three references.
4. (Optional but encouraged) A link to a GitHub repository, portfolio, or example of prior analytic work demonstrating programming or data analysis skills. Applications will be reviewed on a rolling basis until the position is filled. Start date is flexible.