From the article I'd get the impression there should be a huge demand for statisticians to analyze the genome but I'm just not seeing that when I search.
There is also a great need for Software Engineers/Mathematicians to improve the analysis software and the algorithms behind them (primarily string matching) to account for advances in the "chemistry" that companies like ABi and Illumina are making in regards to their sequencing technology.
These are both just on the "production" side of the process - i.e. the processes and people that produce the first round of analysis and statistics from the raw read data (sets of As, Gs, Ts and Cs). Further analysis that looks for SNPs (single nucleotide polymorphisms, what Wade calls 'variant DNA units'), carries out genome annotation and eventually attempts to statistical link both of those results and numerous others to disease traits is carried around by teams of programmers and biologists/geneticists. However, as the data becomes increasingly large and complex so too does the role programmers and clever software play.