The Department of Biostatistics and Medical Informatics at UW-Madison is developing a proposal for a new PhD program in Biomedical Data Science. As part of the proposal, we need to demonstrate the need for the program.

Part of this is easy: huge increase is size and complexity of biomedical data (from genomics-type assays, plus electronic health records) and increased reliance on such data in medical decisions and for health care policy. Also, there have been numerous calls for training in biostatistics and biomedical informatics.

In a January, 2016, article in the Denver Post, Shawn Wang, vice president of data science for Anthem Insurance’s health care analytics department, was quoted as saying, “Data science has been mature for the last couple years in retail, e-commerce and fintech (financial technology). They’re really strong. We have to leverage those. Our preference is to find people within the health care space, but we know there is a limited supply. It’s not easy.”

But we are also asked to provide data on employment opportunities for graduates of the program. This seems a bit more tricky. My main concern is the need to separate data science generally (which is mostly non-biomedical; for example, tech and finance) from biomedical data science in particular.

This page is a list of possible evidence we might present.

Terms to consider:

  • biomedical data scientist
  • biostatistician
  • biomedical informatics
  • computational biologist
  • bioinformatics
  • data scientist
  • statistician