About the Data Science and Analytics Section

The Data Science and Analytics Section of the Statistical Society of Canada was established in 2020.  The Section aims to advance Data Science and Analytics broadly, including the role of statistical science in computing, data acquisition, storage, and cleaning, to finding value in acquired data, enabling evidence-based decisions, producing inference and predictions, and communicating and disseminating domain informed results.


2022 Data Science & Analytics Section Webinar Series

1. Jennifer Zhu (AWS Machine Learning Lab) Information Extraction from Semi-Structured Documents
2. Rob Hyndman (Monash University) Feature-Based Time Series Analysis
3. Will Grathwohl (DeepMind) Deep Learning and Statistics: Best Friends who Help Each Other Out
4. Yannet Interian (University of San Francisco) Multi-task Models to Predict Hypotension and Other Studies
5. Vincenzo Coia (University of British Columbia) Piecing Together the Statistical Puzzle to Build a Model
6. Nathaniel Stevens (University of Waterloo) General Additive Network Effect Models: A Framework for the Design and Analysis of Experiments on Networks
7. Linbo Wang (University of Toronto) The Synthetic Instrument
8. Saif Mohammad (National Research Council Canada) The Search for Emotions, Creativity, and Fairness in Language
9. Stacy Carter (University of Wollongong) The Ethical and Social Implications of Using Artificial Intelligence in Healthcare


2023 - 2024 Executive

President: Matthew Greenberg (2023-07-01 - 2024-06-30)

President Elect: Rohan Alexander (2023-07-01 - 2024-06-30)

Past President: Tiffany Timbers (2023-07-01 - 2024-06-30)

Treasurer: Lam Ho (2023-07-01 - 2026-06-30)

Secretary: Archer Yang (2023-07-01 - 2026-06-30)

Industrial Advisor: Ella Hilal (2021-07-01 - 2024-06-30)


Past Executive


2019-2020: Dave Campbell
2020-2021: Nathan Taback

2021-2022: Nathaniel Stevens
2022-2023: Tiffany Timbers