Report on workforce solutions recognizes TDA at Ohio State

A new report released by the Business-Higher Education Forum and PwC recognizes Translational Data Analytics (TDA) for its partnering with industry to advance Ohio State’s mission and address workforce needs in data science and analytics.

The report, Investing in America’s data science talent: The case for action, was written for businesses in need of workforce talent in data science and analytics, which it defines as “the skills needed to discover, interpret, and communicate meaningful patterns in data.” Among its data sources were a landscape analysis of 26.9 million U.S. job postings from 2015 that identified 2.3 million jobs in data science and analytics, interviews with 1,250 leaders from U.S. colleges and universities, and interviews with 25,683 leaders of businesses across 10 sectors with annual revenues of $10 million or more.

Overall, the report points to a continually growing need for such talent and a dearth of educational programs that speak to that need. It does, however, note a willingness among higher education institutions to rise to meet the need for education and training. TDA is cited as an example of how educators and employers can most effectively come together to meet the talent supply-demand challenge when their larger missions are considered. The report calls the related education programs that result, known as “market-based” programs, “the best formulas for easing the supply-demand challenge” in the data science and analytics workforce.

“Ohio State has excellent programs both for data scientists and for students in other fields for whom the use of analytics is becoming essential,” said TDA Interim Faculty Director Raghu Machiraju. “Our range of expertise and offerings means all of our students can become knowledgeable in deriving value from data, however that may be defined.” Machiraju is also a professor in the Department of Computer Science and Engineering.

Some of the report’s other points:

• Jobs in data science and analytics require a diverse skill set. They require the ability to translate analytics into value for an organization and soft skills like communication and creativity. Ideal candidates are often referred to as “T-shaped,” “with a principle competency, plus well-honed broad skills to help them cross functions or domains.”
• There are two “families” of jobs related to data science and analytics that require different competencies and skills: analytics-enabled jobs and data science jobs. The former, which utilize data analytics in decision-making but have functional expertise outside of data science, represented 67 percent of the job postings. These jobs, the report found, require candidates to have hands-on experience with software for visualizing and reporting data. There is also a need for current employees within various functional areas to increase their “data IQ” to help make operations more effective. Data science jobs, on the other hand, require candidates with programming and applied data science skills, which are in particularly short supply.

Addressing data science and analytics workforce needs is one of TDA’s primary objectives, and TDA faculty in residence Dorinda Gallant and Joyce Wang recently completed an assessment of related programming at Ohio State. They found strong offerings of data-related courses throughout Ohio State’s colleges and major programs, as well as several certifications that support ongoing workforce development. At the forefront is the university’s interdisciplinary data analytics major for undergraduates, which was the first of its kind in the United States.

As a result of their assessment, TDA is leading the development of two new graduate degrees, both in translational data analytics: a professional science master’s degree and an interdisciplinary master’s in science. The PSM program is expected to launch in fall 2018.

“Right from the start, TDA heard from our industry partners that workforce development is a real pain point,” says David Mongeau, TDA’s program director. “They are asking Ohio State faculty and leaders for solutions. We’re responding by keeping the dialogue alive with our students’ future employers to ease their pain, and developing new and evolving existing data science and analytics programs to equip students who are the next generation of innovators.”

original article from Translational Data Analytics