Summary

Who I Am

  • A dedicated scientist committed to applying statistical and machine learning protocols to propel research in genomics and molecular biology.
  • I have an accumulated 21+ years of experience spanning bench scientist support, complex regression modeling, and machine learning research in biotech and public health spaces.
  • I excel in the development of rigorous, original protocols published in peer-reviewed methods journals, and I bring invaluable context with backgrounds in bioinformatics, genomics, clinical medicine, environmental epidemiology, and molecular biology.
  • Working mainly in R and Python, I have flourished both collaborating with and embedded within teams of developers to produce fully functional research pipelines.

Highlights

  • A deep well of experience in statistical methods and applications, including both supervised and unsupervised machine learning in the context of genomics and molecular biology
  • Successful track record in development of statistical and data management protocols contributing to company research pipelines
  • Customary role in research design and analysis to assure of statistical power and validity
  • Fluency in R, Python, and SQL; accustomed to working directly with IT development personnel, including the use of AWS and Docker environments
  • Background in clinical medicine with 21+ years of experience in biostatistics

Education

  • Coursework, Sequence Analysis and Genomics program, Johns Hopkins University
  • PhD in Social Work, University of Illinois at Champaign-Urbana
  • MD, University of Illinois
  • Residency in Pediatrics, New England Medical Center/Tuffs
  • Postdoctorate in Health Service Research, University of California at San Francisco
  • Postdoctorate in General Pediatrics, UCSF
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