Educational and Organizational Challenges of the Data Science Industry (A Case Study)

Data science has experienced enormous growth over the past decade. This growth has created a large demand for talented data scientists in recent years. However, as the data science ecosystem quickly expands, many challenges have become apparent. Some challenges for academia and industry include the difficulty of closing student skill gaps like communication skills, business skills, and real-world project skills. Other challenges for organizations include misalignment of business and strategy and the lack of technical expertise to create value out of data science. In addition, the lack of applicable knowledge about data science, the lack of intuition to build business value, and the constant worry about how data science ethics plays a moral and legal role are all problematic. This research analyzed two publicly available survey datasets to mine insights that could potentially help solve these challenges. The resulting analysis provided insights about students’ needs to be successful, and education’s role in helping create that success. This study provides supporting evidence for existing knowledge and data-backed discoveries that could help the industry solve some of these challenges. Lastly, this research recommends actionable solutions for educators and industry managers to bridge the education-industry gap to produce more successful student data scientists resulting in a higher capacity for organizations to create value out of data science.