Currently, there is a shortage of data wranglers and analysts. Just in time to meet the needs of what could be a revolution in healthcare, WSU is bringing up to speed one of the few data analytics programs in the country. Under the direction of entrepreneur-scientist Nella Ludlow, WSU’s new data analytics program is training the bioinformaticists who will be the genetic counselors and consultants of the future.
Just in its second year—paralleling the new WSU MD program in Spokane—Ludlow’s students are getting jobs as fast as they can get their degrees. She mentions a couple of juniors who got internships with a company that analyzes low-altitude aerial photography for insurance companies wanting to make sure they’re not being defrauded. Post-internship, the students were offered part-time jobs for their senior years in college—and full-time gigs as soon as they graduate.
Part of that success is down to Ludlow herself: she’s got a long track record of partnering with industry. But, she says, it’s also due to a huge demand in every industry sector. “Almost any process that you can collect data on, you can analyze to see how to optimize it, make it safer, cheaper,” she says. “It can literally save companies millions, so they’re willing to invest—which is one of the reasons we are short of data scientists.”
The basic idea is pretty simple: you train a computer to look for patterns in data that might signal something interesting. For instance, you might analyze genomic data to see if people with schizophrenia have an allele, a variant of a gene, in common, one that nonschizophrenics don’t share.
“The first part is to find the needle in the haystack, and once we see the correlation, that could be a clue as to where to search next,” Ludlow says.
Such studies are taking place every day, Ludlow says. Called genome-wide association studies, which look for correlations between a disease and a genetic factor, they produce massive amounts of data. Such studies are only one way of collecting health-related data, though. WSU researchers are pioneering ways of using social media to monitor disease outbreaks, and developing wearable electronic devices that monitor blood pressure, glucose levels, and many other factors that, when they change, signal a possible health problem.
It takes a certain kind of person, Ludlow says, to train a computer to spot potentially significant patterns. Women seem more drawn to data analytics than to computer science, possibly because the job does not begin and end with coding.
“What we’re hearing from students who are drawn to data analytics,” Ludlow explains, “is that I like a little computer science, a little bit of math, a little business, a little machine learning, but it’s all glued together and I get to be the translator and work with people. That’s really what it is: ‘Look at this cool pattern I found! And here’s how you can use it.’ You have to communicate; you’re not just writing code.”
The field is also dramatically interdisciplinary. Sixty-two faculty members currently have appointments in the data analytics program, Ludlow says, drawing on fields as disparate as soil science, economics, health sciences, biology, physics, computer science, math, business, and “all the AI people who do things with machine learning.”
But with all this data floating around, what about security? What about privacy? Tech companies like Google and Facebook commodify and sell user information, so one wonders if we have private lives anymore. That extends to our health and genetic information.