Closing the workforce readiness gap in data science

The transition from classroom learning to professional practice often reveals a gap between education and workforce readiness. While education builds the foundation, such as facts, theories and structured learning, the workforce demands immediate application, sound judgment and adaptability in real time. 

The disconnect is reflected on both sides of the workforce equation. According to Cengage Group’s 2025 Employability Report, 48% of recent graduates feel unprepared to apply for positions in their field, while 40% of employers reported to the World Economic Forum’s Future of Jobs Report 2025 that they struggle to find entry-level workers with the skills needed to succeed. This gap highlights the reality that workplace readiness is not defined by how much someone has learned, but by how effectively they can translate that knowledge into performance when faced with real-world challenges and expectations. 

This challenge is particularly evident in data science, where technological advances and increasing demand for skilled professionals outpace traditional training pathways. “We are generating data at an unprecedented scale — from genomics and medical imaging to wearable fitness devices and other digital technologies,” said Stan Pounds, PhD, St. Jude Applied Biomedical Data Sciences MS Program associate dean and Department of Biostatistics member. “Even with artificial intelligence accelerating analysis, we will not be able to fully realize the insights from this information without more data scientists.” 

Meeting this demand requires more than expanding educational opportunities; it requires rethinking how future data scientists are trained and prepared for the workforce. To close the gap between education and workforce readiness, St. Jude is preparing future data scientists for the realities of the modern workforce through intentionally designed training programs that begin as early as high school. Trainees build foundational skills early and continue to develop them through advanced stages of training. 

Preparation begins early 

St. Jude is investing in professional development long before students reach college. Through a partnership with Memphis-Shelby County Schools, the St. Jude STEMM Education and Outreach Program launched a College, Career & Technical Education course that introduces high school students to foundational concepts in data science, computer programming and biomedical research. 

Beyond classroom learning, students gain experience with real-world datasets and industry-relevant tools while earning certifications in data science programming languages. By using data from the St. Jude Cloud, students are exposed to the same types of data and analytical approaches used in modern biomedical research, providing an early opportunity to explore how data can be used in biomedical research. 

Early exposure is critical because it helps students develop both the technical skills and career awareness needed to pursue opportunities in a rapidly evolving field. Many students may never encounter data science in a traditional classroom setting or fully understand the range of careers available to them. By engaging students early with authentic, hands-on experiences, programs like this help students explore potential career paths, make more informed educational decisions and begin building valuable skills. 

“It is exciting to see students who come in with little or no exposure to data science quickly become engaged once they begin to work with the data,” said Kyle Bichsel, PhD, St. Jude STEMM Education and Outreach Program, Virtual STEMM Academy program manager. “Something clicks, and they start asking deeper questions and really engaging with the work in a way that’s exciting to watch.” 

Over time, these opportunities help strengthen workforce readiness and contribute to a larger and more diverse pipeline of future data scientists equipped to meet the growing demands of healthcare, research and other data-driven industries. 

From academia to application 

While early exposure builds awareness and foundational skills, it represents only the beginning of a journey designed to prepare students for advanced roles. At St. Jude, this continues through a graduate-level education and training opportunity, the Applied Biomedical Data Sciences Master’s program in the St. Jude Graduate School of Biomedical Sciences. 

In the Applied Biomedical Data Sciences MS program, students transition from foundational exposure to full-scale application through an accelerated curriculum followed by an intensive practicum. In many traditional graduate programs, students take coursework and conduct research simultaneously, which often means they are still developing foundational skills and are not yet fully able to contribute. By contrast, the St. Jude model is designed so that students enter the practicum already prepared, allowing them to contribute like full-time data scientists on a research team. 

In this final practicum stage, they work directly with St. Jude faculty to produce a tangible, research-ready product, such as an analytical pipeline, dataset or tool, that contributes to ongoing scientific work. This allows students to move beyond classroom learning and apply their learning to complex, high-dimensional datasets in real-world research environments. This approach is uniquely effective at St. Jude because of the scale and complexity of data being generated across the institution, embedding students in an environment with immediate access to large, real-world datasets. 

“The goal is for students to produce meaningful, high-quality work that can be showcased to employers when applying for jobs and that can also support faculty in publishing or securing grants,” explained Pounds. 

By the time students complete the program, they will have already functioned as practicing data scientists. This combination of theory and applied experience ensures that graduates are ready to transition directly into an active role. 

Being SMaRT about career preparation  

Supporting this framework is the Strategic Milestones and Research Training (SMaRT) Plan, a strategic approach to postdoctoral training and career development designed to strengthen workforce readiness and professional growth. The plan organizes training into defined phases with clear milestones, guiding trainees to set goals, identify activities that support those goals and actively track their progress. 

The SMaRT Plan also supports intentional career preparation by integrating career advising, professional development programming and job market readiness activities. It ensures that trainees are advancing their research capabilities while also preparing to transition into the workforce. 

“A key challenge in workforce development is alignment,” explained Sally McIver, PhD, Academic Programs senior director and creator of the SMaRT plan. “Trainees and mentors often enter with different expectations, and without intentional structure, those gaps can persist. “Trainees and mentors often enter with different expectations, and without intentional structure, those gaps can persist. Through facilitated, case-based discussions, we align goals early and reinforce expectations throughout training, strengthening preparation for real-world professional environments.” 

By aligning training experiences with both scientific and professional expectations, the SMaRT Plan creates an intentional and well-rounded approach to workforce readiness, ensuring trainees are prepared to move from research training into careers through fellowships or direct employment opportunities. 

Closing the gap through a connected training ecosystem 

As data continues to expand in scale and complexity across healthcare and research, the need for skilled data scientists will only grow. Addressing that need requires more than isolated educational opportunities; instead, it requires intentional preparation that develops talent early and provides support through multiple stages of training. 

At St. Jude, that approach is embedded in how students and trainees are taught, mentored and prepared to contribute from the moment they begin. 

“Technical competence is expected,” said Pounds. “The real measure is whether trainees can translate scientific questions into analytical frameworks and return results in a way that informs research decisions — an ability that ultimately defines true workforce readiness.”