“The problem for AI in Europe is not the money is finding the talent” (Leading European AI practitioner)
Data Science, Data Analytics, and Artificial Intelligence constitute the fastest-growing job market for the very highly qualified.
Ph.D. and postdoc target participants
Any Ph.D. or postdoc with a numerate background – e.g., STEM, statistics, econometrics – curious about the opportunities in the industry and startups.
Online workshop – Join from anywhere
All attendants receive the link to the online live meeting. After the event, you receive a link to the workshop materials.
Proof-of-concept
Workshop leads
Dr. Macarena Beigier-Bompadre is a founding member of the AI Guild and a Data Scientist at Kenjo. She has 3+ years of industry experience and also trains staff. Earlier she was a Postdoc at the Max Planck Institute for Infection Biology, Berlin.
Dr. Dina Deifallah is a member of the AI Guild and a Data Scientist who enjoys working on business intelligence issues and data analysis issues. She holds a Ph.D. in Communications Engineering from the American University in Cairo.
Dr. Chris Armbruster is head of #datacareer at the AI Guild, Europe’s leading AI practitioner community. Earlier, he was the Director at Data Science Retreat. He helped roll out digital infrastructures for the 80 Max Planck Institutes while also researching postdoc careers.
Workshop structure
Introduction to the online workshop
The objective is to empower workshop participants to pursue a career in the Data & AI professions. A customizable roadmap is offered for a successful transition.
Examples of PhDs transitioning to a career in Data Analytics, Data Science, and Machine Learning
Together, we look at examples of a successful transition from science to data science and start answering your questions.
The roadmap to getting hired
Together, we query the four essential milestones of the career transition, namely a) exploration of the field; b) domain orientation; c) skills gap analysis and training; and d) career start.
The industry-ready CV or resumé
Let’s look in detail at examples of industry-ready CVs for Data Analytics and Data Science.
Trends in employment, startups, and industry
Data on job growth, startup funding, and industry trends are presented. Moreover, data on starting and median salaries have also been collected by a variety of independent sources.
End of the online eventhttps://www.youtube.com/embed/kOGGhbGqIaE