Friday, November 5, 2021
Using data science to innovate and address emerging needs in official statistics
Abstract
Discussion on the following themes by three experts:.
- Leveraging the power of data science to produce more timely and granular statistics and improve on existing methods to create new high-quality solutions for our data needs.
- Striking the balance in using real-time, open, and unstructured data sources with advanced modeling techniques to partner with traditional methods and produce defendable user-centric results faster and at a lower cost
Panelists: Eric Deeben, Office of National Statistics, Data Science Campus, United Kingdom, Wendy Martinez, Bureau of Labor Statistics, USA and Danny Pfeffermann, Central Bureau of Statistics, Israel
Moderator: Eric Rancourt, Statistics Canada, Canada
Panelist biographies:
Eric Deeben
Eric Deeben is the Technical International Programme Lead and Synthetic Data & Privacy Preservation Techniques Squad Lead at the Data Science Campus of the Office for National Statistics of the UK.
As Technical International Programme Lead, Eric engages with other National Statistical Organisations (NSOs) and international bodies. This is in an effort to exchange new data science methods e.g. machine learning, and implement architecture principles with the objective to move from producing exploration statistics to official statistics.
Eric is a dynamic and highly skilled Solution Owner skilled in achieving business and customer objectives. An excellent communicator with international and multi-cultural work experience across Europe, the Americas and Africa. Eric has presented and lectured across the United Kingdom, Norway, Netherlands, Switzerland and United States. Eric is a notable Project Manager with global delivery experience and is an associate lecturer at Cardiff Metropolitan University Business School.
Eric will be sharing his experiences from his participation and leadership within the international Machine Learning field. He will outline some of the processes in play for managing the impactful implementation of machine learning at the NSO, and the importance of international collaboration.
Wendy Martinez
Wendy Martinez has been serving as the Director of the Mathematical Statistics Research Center at the US Bureau of Labor Statistics (BLS) for eight years. Prior to this, she served in several research positions throughout the US Department of Defense. She held the position of Science and Technology Program Officer at the US Office of Naval Research, where she established a research portfolio comprised of academia and industry performers developing data science products for the future Navy and Marine Corps. Her areas of interest include computational statistics, exploratory data analysis, and text data mining. She is the lead author of three books on MATLAB and statistics. Dr. Martinez was elected as a Fellow of the American Statistical Association (ASA) in 2006 and is an elected member of the International Statistical Institute. She also had the honor of serving as the President of the American Statistical Association in 2020.
Danny Pfeffermann
Danny Pfeffermann is the National Statistician and Director General of Israel's Central Bureau of Statistics (CBS). He is Professor Emeritus of Statistics at the Hebrew University of Jerusalem and Professor of Social Statistics at the University of Southampton. His main research areas are: Analytic inference from complex sample surveys; Seasonal adjustment and trend estimation; Small area estimation; Inference under informative sampling and nonresponse and more recently; Mode effects and Proxy surveys. Professor Pfeffermann published about 80 articles in leading statistical journals and co-edited the two-volume handbook on Sample Surveys. He is Fellow of the American Statistical Association (ASA), the International Statistical Institute (ISI) and the Institute of Mathematical Statistics (IMS) and recipient of several international awards.