Earlier this year, IBM announced plans for a collaboration with The Open Group to develop a “first-of-a-kind” internal program for accrediting data scientists. The program was presented as IBM’s response to a troubling dearth of data scientists (151,000 unfilled data scientist jobs, as reported by LinkedIn). Today, IBM announced that the program has certified more than 140 employees with the position of Data Scientist.
IBM emphasizes that the program (led by Maureen Norton of IBM’s Chief Analytics Office) isn’t just an online course. “[The] program is immersive and includes peer-reviewed project work,” wrote Martin Fleming, chief analytics officer and chief economist at IBM. “It is offered with three levels of certification, and ultimately, certification is awarded through experience-based profiles that are assessed by recognized industry experts in the field.”
Ana Paula Appel, a master data scientist for IBM Research in Brazil, was the first person in her country to earn the new certification, completing the program over the course of four months while working. “It’s a great thing,” she said. “It’s hard to prove you can handle lead projects with clients. Certification gives clients the certainty they’re getting people who can do the job.”
The certification is portable, and IBM highlights how the process brings the data scientists closer to a large community of fellow scientists. “It was nice to talk to them,” said Brian Johnston, a lead data scientist in IBM’s Chief Analytics Office, who was also among the first recipients of the certification. “To get feedback, constructive criticism, and chat about data science careers.”
IBM sees this as part of a larger push toward educating and certifying data scientists. “Last week we, along with the University of Pennsylvania and the Linux Foundation, announced an innovative, first-of-a-kind open source project designed to give universities around the world the tools to build Data Science programs fast,” wrote Fleming.
“IBM is committed to helping organizations fill the widening data science gap in their ranks,” he continued. “Our hope is that these steps, among others, help to build a solid path to sustained AI experimentation, development and deployment. Doing so will speed the journey to AI and help improve business performance, efficiency and growth.”
Author: Oliver Peckham