Moderator: Noa Tamir
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 valuable to understand the context and environment in which you will be working, the required soft skills, and the culture of potential work places. Join our panelists to hear about their personal experiences so far, their understanding of the gap between recent graduates’ expectations and the job itself, as well as some insights to the job market one would need to traverse to get it.
Noa has not only made the transition to data science, but has since supported many in their first steps of their careers. As a former Director of Data Science, and Team Lead, she hired and trained talented academics. Noa is currently an independent consultant, and teaches a M.Sc. Data Science Lab at HTW Berlin, a university of applied sciences.
Dr. Marielle Dado completed a PhD in Applied Cognitive Sciences from the University of Duisburg-Essen, as part of the “User-Centred Social Media” Interdisciplinary Research Training Group (“Graduiertenkolleg”) of the German Research Foundation (“Deutsche Forschungsgemeinschaft”). A psychologist and educator by training, she has been working as a data scientist since 2018 and is currently focusing on data integrity and governance within organizations.
PhD Computer Science | Freelance data scientist / researcher
/ teacher | interested in exploring the breaking points of AI systems
(aka hacking the AI)
After studying Theoretical Physics I completed a PhD in Neuroscience at the Uni. of Magdeburg, followed by a postdoc at the Gatsby Computational Neuroscience Unit (UCL) during which gradually strayed away from Neuroscience and towards ML/AI. This eventually led me to a Data Science position at GroupM Data & Technologies, where I have now been working for a year.