Name: For the overwhelmed data scientists: What to do when there is so much to do?
Start: 2021-03-20T17:00:00-07:00
End: 2021-03-20T18:00:00-07:00

95% of the companies with data science teams have teams of fewer than ten members. In a nimble team with a wide range of possibilities to make business impacts with data science, how do you explore and prioritize the opportunities? How do you ensure that there are sponsors and champions for your project? How do you set realistic expectations with business partners for project success? If you are leading a team, how can you delegate your projects effectively?

In this talk, we share three techniques for project prioritization, two roles (sponsor and champions) to identify, four levels of confidence (for predictive models) to specify project success, and discuss best practices for delegating work as a team lead/manager.

Speaker Bio:
Dr. Jike Chong built and grew multiple high-performing data teams. As a key executive who took Yiren Digital Ltd public on NYSE, he built and led the YRD data team from the ground up. He also expanded and led the data team as the Chief Data Scientist at Acorns, designed and executed a project predicting venture investment risks at Silver Lake, and recently led the Hiring Marketplace Data Science team at LinkedIn serving a business line with $4B a year in revenue.

Dr. Chong developed and taught a graduate-level course on Machine Learning for Internet Finance at Tsinghua University, and previously was an adjunct professor and PhD advisor in Electrical and Computer Engineering at Carnegie Mellon University. He received his bachelor’s and master’s degrees in Electrical and Computer Engineering from Carnegie Mellon University, a Ph.D. from the University of California, Berkeley, and holds 11 patents (6 granted, 5 pending).

Speaker's LinkedIn:
https://www.linkedin.com/in/jikechong/

Register event through this link:
https://us02web.zoom.us/webinar/register/7116153406813/WN_6OjbLLixS1GmNOJy63ZlXw

Jason Geng

Glendale School of AI

Technology

Artificial Intelligence

New Technology

Machine Learning

Neural Networks

Artificial Intelligence Applications

AI and Society

Artificial Intelligence Machine Learning Robotics

D.Hajj (Precognist)

Andrews Samuel

irshad

Melinda B. Chu

Eric Yun

Jill Carrigan

For the overwhelmed data scientists: What to do when there is so much to do?

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Glendale School of AI

For the overwhelmed data scientists: What to do when there is so much to do?

Glendale School of AI

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