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In October 2012, the Harvard Business Review published an article calling data science the “sexiest job of the 21st century”, and comparing data scientists with the ubiquitous Wall Street “quants” of the ’80s and ’90s: a data scientist is a “hybrid of data hacker, analyst, communicator, and trusted adviser.

Would-be data scientists are usually introduced to the field via machine learning algorithms and applications. Much could be said about those; the material presented here is not meant to constitute a complete survey of the field (multiple references are provided for the interested reader).

Data Science Report Series #10: Data Science and Machine Learning (Draft), by Patrick Boily, Jennifer Schellinck, and Shintaro Hagiwara.

Post Author: Patrick Boily

Patrick is a graduate from the University of Ottawa. He obtained his Ph.D. in Mathematics in 2006. He has taught over 35 courses at Universities in the Ottawa area since 1999, and worked on a number of projects as a federal public servant from 2008 to 2012. He joined Carleton University in 2012 to start and manage the Centre for Quantitative Analysis and Decision Support (CQADS), and is an Adjunct Professor at both the University of Ottawa and Carleton University. He is the president of Idlewyld Analytics and Consulting Services since 2016.

Patrick’s academic interests reside in the application of mathematics and statistics to evidence-based decision support. He has provided consulting services to numerous entities over the years, including United Way, the Public Health Agency of Canada, the Canadian Air Transport Security Authority, the Royal Canadian Mounted Police, Transport Canada, the Nuclear Waste Management Organization, the Privy Council Office, and Correctional Services Canada.

He has extensive experience in operations research, data science and predictive analytics, stochastic modeling, and simulations – managing and being involved in numerous projects in these subject areas from inception to completion. He also leads various workshops and training courses on data science and statistical analysis through the Data Action Lab.