On Transitioning from Academia to Data Science

When hearing about transitioning to a data science job, one is often faced with a list of technical skills: from programming packages and frameworks, to applied statistics topics, and data visualizations. But making the transition to data science is not only about technical competencies. It is also valuable to understand the context and environment in which one will be working, the required soft skills, and the culture of potential work places. Most of these cannot be found in job descriptions and data science courses. I will present my understanding of the gap between recent graduates' expectations and competencies and the job itself, as well as some insights into the job market they would need to traverse to get hired. In addition, I will share my teaching approach as a career mentor and a university teacher. I have not only made the transition to data science, but have since supported many in their first steps of their careers. As a former Director of Data Science, and Team Lead, I hired and trained talented academics. I am currently an independent consultant, and teach a M.Sc. Data Science Lab at HTW Berlin, a university of applied sciences.