Palestra: Painel: Ask Me Anything about Data Science

Gleicon Moraes atua construindo e consertando sistema distribuídos e de larga escala há mais de 20 anos, mantém projetos opensource em Python e Go. Se interessa por problemas de sistemas de larga escala e volume de dados. Escreveu dois livros: “Programação Avançada em Linux” em 2005 pela Novatec e “Caixa de Ferramentas Devops” pela Casa do Código. Trabalhou em empresas como Terra, UOL, Locaweb, Luizalabs e Lucid. Atualmente é VP de Engenharia no Nubank.

Thierry did a double Master degree in Computer Science from ESIEA (French Engineer School) in France and the Illinois Institute of Technology in Chicago, USA. After that he worked for a startup in Paris for 6 months before starting a PhD at the University of Konstanz in Germany on Recommendation System working on libFM. Today he works as a Tech Lead Data Scientist on different kinds of project ranging from improving customer service, understanding growth, improving processes and managing other data scientists. He is also the co-organizer of the Machine Learning Meetup in Sao Paulo which is the biggest in Latin America.

Chakri Cherukuri is a senior researcher in the Quantitative Financial Research group at Bloomberg LP. His research interests include quantitative portfolio management, algorithmic trading strategies and applied machine learning. Previously, he built analytical tools for the trading desks at Goldman Sachs and Lehman Brothers. Before that he worked in the Silicon Valley for startups building enterprise software applications. He has extensive experience in scientific computing and software development. He is a core contributor to bqplot, a 2D plotting library for the Jupyter notebook. He holds an undergraduate degree in mechanical engineering from Indian Institute of Technology (IIT), Madras, an MS in computer science from Arizona State University and another MS in computational finance from Carnegie Mellon University.

Dhiana Deva é Machine Learning Engineer no Spotify. Trabalhou anteriormente em organizações como ThoughtWorks e CERN (Centro Europeu de Pesquisas Nucleares). Após ter treinado sua primeira Rede Neural há mais de 10 anos atrás e trabalhar no maior centro de pesquisas do mundo, Dhiana explorou o mundo Agile e Lean em experiências como Software Engineer em start-ups e consultoria - mas seguiu introduzindo Data Science e Machine Learning nos produtos que tocou. Há 3 anos trabalhando no Spotify, onde começou como Software Engineer e foi demonstrando e introduzindo aplicações de Machine Learning em seu time, conquistando a posição de Machine Learning Engineer.

Eric Wayman is a Senior Data Scientist at Salesforce. As a member of the Einstein AI platform team, he works on developing the automated machine learning Pipeline for the recently released Einstein Prediction Builder, which helps Salesforce administrators leverage their Salesforce data to make predictions for use cases tailored to their individual needs. Before joining Salesforce, Eric worked as a Data Science Consultant at Pivotal Software and also did research in Probability and Stochastic Processes at UC Berkeley where he received his Ph.D. in Mathematics.