10,000 Data Scientists for Europe

On a Friday at 11 CEST. 60 minutes. 500 seats. Join the experts in discussing the deployment of data analytics and machine learning. Hear how you can scale out of the recession with the data economy. Benefit from the AI Guild team effort showing use cases in production. Program for 27 November 11.00 Welcome to the #datalift No 2 by Dânia Meira and Dr. Chris Armbruster (AI Guild) Key interview: Dr. Francçois SIllion, Director, Uber ACTP François Sillion is the director of Uber’s Advanced Technologies Center in Paris, focusing on applications to air transport. Uber Elevate’s vision includes machine learning, airspace management, sensing & perception, autonomous control, energy management, and communication networks. Earlier, François was a senior research and director at INRIA. His work has >9500 citations and he has an H-index of 48. Use case in production Use Case 1 Rachel Berryman, Data Scientist, AI Center of Excellence, Elia Group Deploying the first Neural Network in energy transmission service: The Elia Group TSO use case" Use Case 2 Dr. Sebastian Rose, Senior Data Scientist, MYTOYS GROUP "Machine learning in production: The MYTOYS product list sorting algorithm" Use Case 3 Markus Hinsche, Senior ML Engineer, Freelance (for Welthungerhilfe) "Zero Hunger by 2030! How anthropometric measurement helps make the dream a reality." Use Case 4 Mahmoud AbdelAziz, Founder & CEO, DevisionX "AI-Machine Vision Quality Inspection Solutions for Manufacturers without Coding, without AI experience by Using TUBA enabling tool: Label, Train, Integrate That's it!"

Data Science, Data Analytics, and Artificial Intelligence constitute the fastest-growing job market for the very highly qualified. - How do I find out if a career in data analytics or data science is right for me? - A customizable roadmap for completing the transition in 6 to 9 months - Tips and tricks on approaching the labor market and hiring managers Ph.D. and postdoc Target participants Any Ph.D. or postdoc with a numerate background - e.g. STEM, statistics, econometrics - that is curious about the opportunities in the industry and in 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 - An ongoing event series since 2018 in university towns and online, including repeated collaboration with the Max Planck Society, and the Max Planck PhDNet, Helmholtz Juniors, and the Leibniz PhD Network. - We have supported >200 data talents with managing the transition and writing an industry-ready CV - You can look at the workshop slides prepared for the 2019 N2 conference of the Max Planck PhDNet, Helmholtz Juniors, and Leibniz PhD Network. The slides are available on Slideshare. Workshop leads Dr. Macarena Beigier-Bompadre is a founding member of the AI Guild and a Data Scientist at modellagenten. 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 at HeyJobs that also enjoys working on issues of business intelligence and data analysis. She holds a PhD in Communications Engineering from the American University in Cairo. Dr. Chris Armbruster is a founding member of 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 18.00 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. 18.10 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. - What are the typical starting points for the transition? - How large is the opportunity and what are the requirements for a #datacareer? - How do you move to the industry, startups, or a consultancy firm? - What is the outlook for a #datalift in Europe? 18.30 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. - Roadmap for the transition - Interactive Q&A via online chat 19.00 The industry-ready CV or resumé Let's look in detail at examples of industry-ready CVs for Data Analytics and Data Science - Examples and stories - Interactive Q&A via online chat 19.20 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. - Presentation of data and trends - Final Q&A via online chat and video 19.30 End of the online event