Episode 33
Supply Chain Solutions and the Role of the ML Engineer
Data Science Leaders | 38:04 | January 12, 2022
When highly disruptive events like the COVID-19 pandemic occur, data science teams may have to throw historical data out the window. Models trained on what happened in the past simply don’t work in a radically different present.
In this episode, Karin Chu, VP Data Science and Digital Analytics at Peapod Digital Labs, discusses how her team is tackling that challenge head on, particularly as the global supply chain crisis impacts sectors from grocery to apparel.
Plus, she explains why two things are so vital to the success of a data science team: ML engineers and a culture of communication.
When highly disruptive events like the COVID-19 pandemic occur, data science teams may have to throw historical data out the window. Models trained on what happened in the past simply don’t work in a radically different present.
In this episode, Karin Chu, VP Data Science and Digital Analytics at Peapod Digital Labs, discusses how her team is tackling that challenge head on, particularly as the global supply chain crisis impacts sectors from grocery to apparel.
Plus, she explains why two things are so vital to the success of a data science team: ML engineers and a culture of communication.
We discuss:
- How data science teams are navigating the supply chain crisis
- The vital role of an ML engineer
- Tips for communicating about data science in business
