Who is Data Scientist and how to become one? [Discussion]
Among the speakers and participants of the conference there are technical experts, engineers from the Data Science field or those who would like to develop in this direction. They will be interested in discussing the topic of how to become a Scientist. What you need to know, what to learn, what skills to get. What knowledge is especially in demand in companies where experts work. What is need for young professionals.
Vote and propose your topic here - https://app.sli.do/event/n86u8voj/live/questions
Moderator: Ian Tsybulkin (Co-founder Bldbox)
Experts:
- Vladimir Kubytskyi (Head of AI-Team @ LUN | Flatfy)
- Oleksii Sliusarenko (Senior NLP engineer @ Deloitte)
- Evgen Terpil (Head of Data Science squad @ YouScan)
- Taras Lehinevych (Machine Learning Engineer @ Rails Reactor)
Evgen Terpil
YouScan
- Head of Data Science squad at YouScan.
- Teaches different models for NLP and CV tasks.
- Interested in Deep Learning and Social Network Analysis.
Volodymyr Kubytskyi
LUN
- Head of AI / Chief Innovation Officer at LUN and bird
- Candidate of PhD in Computer Science
- Author of scientific publications on the use of convolutional neural networks for image comparison
- The author of the annual ML internship under the KNU+LUN dual education program
Taras Lehinevych
Rails Reactor
- Machine Learning Engineer at Rails Reactor
- Lecturer at National University of Kyiv-Mohyla Academy and Rails Reactor Machine Learning Summer School
- PhD student in Computer Science at the IPS NAN of Ukraine and NaUKMA
Ian Tsybulkin
Bldbox
- Technology entrepreneur
- Co-founder Cloudozer, Symica, Bldbox
- Lecturer of course: Linear Algebra for Data Science
- Author of the course at Projector: Mathematical basics of Data Science
- AI and robotics enthusiast
Oleksii Sliusarenko
Deloitte
- Senior NLP engineer at Deloitte
- Data scientist with 8 years of experience in machine learning and NLP
- Winner of international math and programming competitions. Worked at Ukr.net, Grammarly
- Has experience in various algorithms from rule-based approaches to modern deep learning methods. Currently, he works on NLP projects for business optimization