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Xiao-Li Meng: “Being, Training, and Employing Data Scientists”
Being, Training, and Employing Data Scientists: Wisdoms and Warnings from Harvard Data Science Review
On March 21, 2024, the Department of Mathematics and Statistics and the Faculty of Arts and Science at Queen’s University in Kingston, Ontario, will host a distinguished lecture with Xiao-Li Meng, Founding Editor of Harvard Data Science Review and one of the world’s leading statisticians.
CANSSI is proud to be a sponsor of this unique event.
The lecture will be presented in a hybrid format to enable both in-person and online attendance and will be preceded by a reception for in-person attendees. We hope you’ll be able to join us!
Registration
We invite you to register for the lecture on Eventbrite. You will be asked to indicate whether you are planning to attend in person or online.
Schedule and Location
The lecture will be held in Jeffery Hall 127, 48 University Avenue, Queen’s University, in Kingston, Ontario.
The reception for in-person attendees will be held in front of Room 127 in Jeffery Hall.
5:00–5:30 p.m. EDT | Reception (for in-person attendees)
5:30–6:30 p.m. EDT | Lecture
Lecture Abstract
“What Does It Take to Be a Successful Data Scientist?”
“Is Data Science Education a Jack of All Trades?”
“How Can We Train Data Scientists When We Can’t Agree on Who They Are?”
These thought-provoking questions are the titles of articles in Harvard Data Science Review (HDSR). This talk surveys and reflects on data science training, employment, and deployment in the BIG (Business, Industry, and Government) world based on such articles, and many more:
- “Change Through Data: A Data Analytics Training Program for Government Employees”
- “Beyond Unicorns: Educating, Classifying, and Certifying Business Data Scientists”
- “Toward Foundations for Data Science and Analytics: A Knowledge Framework for Professional Standards”
- “From Unicorn Data Scientist to Key Roles in Data Science: Standardizing Roles”
- “Deployment as a Critical Business Data Science Discipline”
- “When Translation Problems Arise Between Data Scientists and Business Stakeholders, Revisit Your Metrics”
- ”How to Define and Execute Your Data and AI Strategy”
- “A Balanced Perspective on Prediction and Inference for Data Science in Industry”
- “What Are the Values of Data, Data Science, or Data Scientists?”
- To Deploy Machine Learning, You Must Manage Operational Change—Here Is How UPS Got It Right.
About Xiao-Li Meng
Xiao-Li Meng, the Founding Editor-in-Chief of Harvard Data Science Review and the Whipple V. N. Jones Professor of Statistics at Harvard University, is well known for his depth and breadth in research, his innovation and passion in pedagogy, his vision and effectiveness in administration, as well as for his engaging and entertaining style as a speaker and writer. Meng was named the best statistician under the age of 40 by the Committee of Presidents of Statistical Societies (COPSS) in 2001, and he is the recipient of numerous awards and honours for his more than 150 publications. In 2020, he was elected to the American Academy of Arts and Sciences. Meng received his BS in mathematics from Fudan University in 1982 and his PhD in statistics from Harvard in 1990. He was on the faculty of the University of Chicago from 1991 to 2001 before returning to Harvard, where he served as the Chair of the Department of Statistics (2004–2012) and the Dean of the Graduate School of Arts and Sciences (2012–2017).