Carlos Andre Reis Pinheiro
Principal Analytical Training Consultant, SAS
Dr. Carlos Pinheiro is a Principal Data Scientist at SAS and a Visiting Professor at Data ScienceTech Institute in France. He has been working in analytics since 1996 for some of the largest telecommunications providers in Brazil in multiple roles from technical to executive. He worked as a Senior Data Scientist for EMC in Brazil on network analytics, optimization, and text analytics projects, and as a Lead Data Scientist for Teradata on machine learning projects. Dr. Pinheiro has a BSc in Applied Mathematics and Computer Science, an MSc in Computing, and a DSc in Engineering from the Federal University of Rio de Janeiro.
Carlos has completed a series of postdoctoral research terms in different fields, including Dynamic Systems at IMPA, Brazil; Social Network Analysis at Dublin City University, Ireland; Transportation Systems at Université de Savoie, France; Dynamic Social Networks and Human Mobility at Katholieke Universiteit Leuven, Belgium; and Urban Mobility and Multi-modal Traffic at Fundação Getúlio Vargas, Brazil. He has published several papers in international journals and conferences, and he is author of Social Network Analysis in Telecommunications and Heuristics in Analytics: A Practical Perspective of What Influence Our Analytical World, both published by John Wiley Sons, Inc.
By This Author
Introduction to Statistical and Machine Learning Methods for Data Science
By Carlos Andre Reis Pinheiro and Mike Patetta
This book provides a comprehensive overview of the statistical and machine learning techniques associated with data science initiatives. You will learn the most important techniques and methods related to data science and when to apply them for different business problems.
"A comprehensive and nifty book that takes the reader through the analytics lifecycle, discussing many data science methods, statistical approaches and machine learning techniques. The variety of case studies and tips along the way enhances your knowledge and capability, forming a practical understanding of data science".
Michelle Homes, Metacoda
Australia
Heuristics in Analytics: A Practical Perspective of What Influences Our Analytical World
By Carlos Andre Reis Pinheiro and Fiona McNeill
A practical guide to deploying mathematical and statistical models when performing analytics. Packed with case studies on the entire analytical process using telecom and insurance companies based in Brazil and Ireland, Heuristics in Analytics provides CFOs, chief marketing officers, directors of marketing, and business managers with an insider guide to deploying mathematical and statistical models when performing analytics.
Social Network Analysis in Telecommunications
By Carlos Andre Reis Pinheiro
Looks at social network analysis theory, employing basic statistics as a complementary way to analyze social networks. Case studies are presented demonstrating the capabilities of SAS in achieving business results. Provides the groundwork for what social network analysis is, as well as how your company can leverage it to its greatest advantage.
Featured Authors
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Todd Case has been working in the pharmaceutical industry as a statistical programmer for over 20 years. He completed his MS in Epidemiology from Columbia University and has worked at Forest Laboratories (now Allergan), Genentech, Bristol-Myers Squibb, and Biogen. He currently works at Vertex Pharmaceuticals.
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Terisa Roberts is a director and Global Solution lead for Risk Modeling and Decisioning at SAS. She has extensive experience in quantitative risk management, regulatory compliance, and model governance and validation. She has worked in financial services, telecommunications, government, energy, and retail sectors.
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Ron Klimberg, PhD, is a professor at the Haub School of Business at Saint Joseph's University in Philadelphia, PA.
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Robert N. Rodriguez retired from SAS in 2018 after serving as a senior director in research and development. Bob received a PhD in statistics from the University of North Carolina at Chapel Hill and was a research statistician at General Motors Research Laboratories before joining SAS.