Data, But Verify: How Montgomery College Used Job Postings & Employer Conversations to Develop Data Science Program

Summary

Dr. Kevin Long, director of policy and planning at Montgomery College, spearheaded a two-year project to develop a brand new, year-long data science certificate program.

Highlights 

• Long used job posting data to determine the specific skills needed by employers.
• The Montgomery College team authenticated Long’s findings through conversations with employers.
• Solid intel allowed the college to design a streamlined program by which industry workers can quickly upgrade their skills.

Creating the Right Data Science Program for the Region

Who is “part mathematician, part computer scientist, and part trend-spotter” and straddles business and IT to solve complex business problems by analyzing scads of data?

That would be data scientists.

Comfortably swimming in datasets that would sink many others, these analysts study the market, build products, generate sales, support clients and employees, and can more or less make or break a company. No wonder their job has been named the sexiest of the 21st century. And it’s a job desperately needing new talent in the region surrounding Montgomery College.

“I saw increasing demand for big-data skills in Montgomery County in particular—that’s what tipped me off,” said Dr. Kevin Long, director of policy and planning at the college with three campus locations (Germantown, Rockville, Takoma Park) in southern Maryland. The demand that caught Long’s eye is at least partly explained by Montgomery College’s proximity to business-rich Washington, D.C. “But despite employer demand, there were no data science credentials in the area.”

Montgomery College stepped up. After a two-year process that involved drilling deep into job posting data and verifying the analysis through follow-up conversations with regional employees, a brand new, year-long data science certificate program is set to launch in spring 2018.

Sensing the Need

For Long, the jumping-off point was the critical question—What is the actual need? Companies reported a lack of market research analysts and data analysts, yet Long was suspicious that employers weren’t after particular job titles, but a particular skillset. He was right. And it wasn’t the skillset you might expect.

The requested jobs included market research analysts and data analysts—jobs that would seem to fall within big-data analytics, but that actually involve handling corporate data to make marketing decisions. So Long’s first step was determining the skills these jobs had in common. What he discovered was a profusion of hard-core technical skills and data-base programming skills: Apache, Hadoop, Python…. Employers might not have advertised for data scientists, but that is what they were looking for.

“We realized, businesses aren’t searching for job titles, they’re searching for these skills—and these skills really need a data science program,” Long said. “Then we had to decide, how can we assemble a quick-sequence certificate for big-data workers so they can upgrade their skills?”

To answer this, Long first determined the skills that workers might reasonably be expected to already possess—skills that Montgomery could then supplement. “Folks may have computer skills, but not statistical analysis skills to go with it; or they may have the statistical analysis skills, but not not the computer programming skills to go with it,” Long said. “And almost certainly no one has the all-important data visualization skills.”

Confirming With Employers

Meanwhile, the vice president provost at Montgomery’s Germantown campus and the dean of the mathematics department presented the data to local employers to see if it resonated. It did.

“That was the benefit of having access to this kind of data,” Long said. “We had solid intel that rang true with real people. Prior to this, businesses had proceeded from mere anecdotal evidence: ‘We need this and that.’ What a powerful switch for us to be able to use their anecdotes not as evidence per se, but as a starting point for cultivating evidence.”

Designing the Program

With both labor market data and boots-on-the-ground opinion on their side, Montgomery College designed the new curriculum to focus on emerging, in-demand skills. What was first imagined as a certificate program quickly dilated into both a certificate program, which targeted industry workings looking to enhance their skills, and an internal sequence of programs related to data science geared for students needing those one or two classes before transferring to a four-year institution, or for students seeking a crash course on data science.

(The new certificate program wasn’t the only program boosted by Long’s findings. Based on the specific big-data skills that were advertised, Montgomery was also able to quickly add new courses and course sequences to its workforce development and continuing education program.)

Ingenuity and efficiency was the name of the game. Rather than starting from scratch on new classes, Montgomery utilized existing database and data analysis classes, with a few tweaks and additions. But the coolest part was that the skills rested on top of industry workers’ current credentials. Once Long saw that the data science skills required by employers required a bachelor’s degree (minimum) in data, infrastructure, analytics, or the like, it was a no-brainer. “You can’t come in off the street, get the certificate, and go get a job,” Long said. “We had to offer a program that stood on the shoulders of another degree.”

Building a curriculum that assumed a BA-level of knowledge at the start blocks allowed Montgomery to jettison a number of skills and tighten the program’s time frame. Everything was done with speed in mind for the sake of the key audience: workers in the field looking to rapidly upgrade their skills. Students can use the program as a credentialing pathway to supplement existing skills, or as a focus pathway to another credential.

Success

As a final step, Long confirmed high anticipated growth of the target occupations within a 50-mile radius. With that, the state approved the program.

“It’s a great example of how exploring the data and authenticating your analysis with employers should always go hand in hand,” said Long. “It also demonstrates that you can’t always take job postings at face value. Employers might request X, but they don’t know they need Y. Colleges have to figure that out so they can keep programs relevant to the region’s true needs.”

For more about Emsi’s data and analytics for higher ed, see here. Contact Rob Sentz at [email protected] with questions. Follow us @desktopecon. 

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