Master of Science in Data Science: 5 ways Cabrini is solving the big data talent gap

 

The field of data science may still be in its infancy, but that won’t be the case for long. Studies show the field is in high demand, with stunning growth projected. For now, however, supply needs to catch up with demand. A big data talent gap is in full effect, with businesses looking for data scientists when there simply aren’t enough to go around.

According to a recent Burning Glass Technologies report, the average Data Science and Analytics (DSA) job posting remains open for 45 days – five days longer than the market average. Employers are having a tough time finding qualified applicants – which is good news for data professionals who possess the right skills. 

The limited supply of qualified applicants is also driving up salaries, with the average Data Science and Analytics role advertising an annual salary of $80,265 – over $8,000 more than other bachelor- and graduate-level jobs. Businesses are willing to pay a premium for these hard-to-find employees.

Why employers struggle to find qualified data scientists

The big data skills gap isn’t as easy to address as it may seem, largely due to the hybrid nature of the data scientist role. DSA jobs require a unique mix of advanced analytics abilities as well as deep knowledge in business insights, complex data strategy, and communication. 

That’s why nearly 40% of employers are seeking applicants with a Master’s in Data Science. Many DSA job applicants with experience in typical data analytics roles do not exhibit the hybrid skills employers need. Hiring managers want proof that applicants can offer an added layer of strategy, insight, and communication to the job.

5 Ways Cabrini’s online Master of Science in Data Science degree helps close the talent gap

Recognizing this workforce trend, Cabrini University set out to provide a solution for employers and employees throughout the New England region and across the U.S. 

“We already have a very strong undergraduate program and great faculty here in the Department of Computer and Information Sciences,” says Dr. Daniel Wu, “but there is a need for Data Scientists with an enhanced skillset.” As the Program Director of Cabrini’s pioneering online Master of Science in Data Science degree program, he’s expanding the department’s offering in a meaningful way. 

“We’re building a data science program that is practical, so that when students graduate, they’ll have a solid foundation for getting the next job and performing well.” What’s the key to achieving that goal? Read on for a few ways this program is tackling the data science talent gap.

1. Focusing on industry-standard tech skills, business theory, and insight

Cabrini’s Master of Science in Data Science program is accounting for an interesting new mix of skills – skills employers are looking for. Everything from writing code as a developer to statistical analysis to visualization is covered by this progressive curriculum. And Dr. Wu is careful to point out the added layer of non-technical skills as well.

“To be a good data scientist, of course you need the technical skills, but you also need a ton of non-technical skills. You need curiosity. You have to tell the story. You need to know what questions to ask and how to communicate the results articulately to anyone. We’re teaching students in all of these areas and connecting them together.”

“It’s true, you could get a single technical skill from anywhere,” says Dr. Wu, “but to combine them and also know how to apply them in a meaningful way is unique to a master’s degree.”

2. Staying in front of industry trends so technology professionals can prepare for careers of the future

Technological innovations are always on the horizon, and with them come new understandings of life with an abundance of data – and the ethical dimensions of how that data is used.

“Right now, machine learning is really big,” Dr. Wu explains. “And how to apply machine learning to the data science field is a challenge that a lot of industries are trying to pursue.” Cabrini’s program weaves in these complex topics, so graduates will be prepared to evolve once they enter the field. 

“Every industry – from marketing to hospitals and pharmaceuticals – they’re all needing to use predictive models and scientific computation. More and more machine learning and artificial intelligence is being used by regular businesses.” According to Dr. Wu, these new trends simply can’t be ignored by aspiring data scientists. They are critical components for any quality data science degree program.

3. Providing internship opportunities and capstone projects that help students graduate with something to show employers

It’s true that there are individuals who grow into data science roles without a formal education. But, they still have to prove their abilities with tangible skills, leadership, business insights, and real-world experience. It can be hard to check all those boxes without the kind of clear path you get with a formal education.

Dr. Wu stresses the importance of getting that experience in your degree program. “Uncertainty is always a challenge. You might derive a lot of different conclusions from data if you apply different methods of gathering.

“The key is to try to reduce all the uncertainty and look at what can really drive business success. A capstone project challenges students to solve for those problems and apply those skills right away.”

4. Connecting to the business community, so students can network and grow into those valuable positions

Like it or not, career progress is at least partly about who you know. Cabrini’s program emphasizes opportunities to network, and the school’s proximity to big industries in New England and the Mid-Atlantic states help them build those connections – even for students earning their degrees online. “We’re collaborating with the business community in multiple ways through this program,” says Dr. Wu. 

He is not only working with the business department at Cabrini to develop curriculum for must-have non-technical leadership skills, but his team is fostering relationships with local and national businesses as well. “The capstone project is informed by local employers and employers across the country, so students can have immediate prospects after graduation.”  

5. Making it possible for working professionals to get the necessary education

Your typical Data Science role is not going to be an entry-level position. That means employers are looking for individuals with both education and experience in real-world situations. To develop these qualified applicants, there needed to be a way for individuals already working in data-centric roles to access relevant education and take that next step in their careers.

Cabrini designed their M.S. in Data Science program with flexibility and efficiency in mind. Courses are offered fully online in an accelerated format, allowing students to take one course at a time while still following a full-time schedule. The entire program can be completed in 24 months. And, at just $665 per credit hour, this program is among the most competitively priced in this burgeoning field.

Explore the advanced degree for data scientists

With the big data talent gap disrupting the industry, astute computer science graduates and working data analysts have a clear opportunity to be pioneers in their field.