A piece at O'Reilly Radar makes some excellent points about employers focusing too narrowly on technical skills in hiring, making it virtually impossible to find the exact perfect candidate, the "purple squirrel" that recruiters deridingly speak of.
That could be especially true when it comes to data scientists. With the rise of Big Data, everyone's looking to hire them, but there are too few to go around.
Writer Mike Loukides makes the point that data scientists can come from a number of scientific disciplines: physics, biology, medicine, meteorology and others. Jeremy Howard, chief scientist of Kaggle, the startup that runs data prediction competitions, has a degree in philosophy. He writes:
The key job requirement in data science (as it is in many technical fields) isn’t demonstrated expertise in some narrow set of tools, but curiosity, flexibility, and willingness to learn. And the key obligation of the employer is to give its new hires the tools they need to succeed.
Indeed, startup Pikimal has turned to hiring philosophy majors and turned them into Ruby developers.
Recently, David Smith, vice president of marketing at Revolution Analytics, talked with my colleague Loraine Lawson about using an interdepartmental committee — basically a competency center model — to fill the talent gap. My colleague Mike Vizard has written that the shortage of data scientists might be filled from the ranks of database adminstrators.
Too often, companies, in addition to looking for the exact skills for a job, are unwilling to allow workers to grow into jobs, as University of Pennsylvania professor Peter Cappelli has written. That contributes to their frustration. A shortage of talent calls for creative thinking, though, and that might pressure companies being more open to accepting, perhaps, a lavender squirrel instead of a purple one.