Last year I moderated a panel on machine learning and big data in e-commerce at the Data Natives conference in Berlin, Germany. The panelists were Cedric Archambeau, senior manager of machine learning science at Amazon, and Lina Weichbrodt, data scientist at Berlin-based e-commerce giant Zalando.
The folks at Data Natives just posted the session recording, which I’m happy to share here.
Machine Learning Issues in E-Commerce
Listen in to our discussion to learn:
- How is data science organized at Amazon and Zalando?
- Where are they applying machine learning and advanced analytics in the business?
- How do they manage the data science lifecycle, and get models into production?
- What metrics do they optimize for? How do they balance short- and long-term business goals in their ML models?
- How do they create a company culture supporting data science?
- Where does big data come into play, and how do they deal with it?
- How is cloud computing used to support their efforts?
- What techniques are used to ensure privacy?
- What approaches are they taking to broaden the adoption of data science within their organizations?
- How do design and usability intersect with predictive analytics?
- Where are the biggest opportunities for analytics and big data in e-commerce?
I’ll be talking to more data scientists and machine learning users over the upcoming months, and sharing those discussions here. If there are things you would like to know or industry use-cases you would like me to explore, please let me know in the comments.