Isabel specializes in developing statistical and data science methods to draw insights from complex data sources. She has worked extensively with clinicians and health officials in the United States and Tanzania to improve access to quality reproductive healthcare.
As VP of Data Science, she will harmonize rich data sources, innovative data science tools, and the vast clinical expertise at Delfina to build patient-centered technologies that improve pregnancy care for all birthing parents. Isabel has a Ph.D. in biostatistics from Harvard University and is currently a Harvard Data Science Initiative Fellow.
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