Raising the Data Science Bar with Cross-Team Collaboration


In modern data stacks the Data Science team has a range of responsibilities to help increase operational efficiency and product effectiveness. We’ll walk through some of the approaches that successful teams employ at Amazon, AWS, and Netflix use to succeed on these fronts. In particular the talk will explore how Notebooks can and should be used as a medium of communication between teams with varying expertises, what this pattern enables, and when to use collaborative technologies. We’ll also describe why you should start thinking about collaboration as a core responsibility of Data Science before you discover this is a bottleneck to your team’s effectiveness.


Matthew Seal is a co-founder and CTO of Noteable, a startup building upon his prior industry-leading work at Netflix. He began his career at OpenGov and helped build their data platform before quickly rising to lead architect. He then went to Netflix, where he had an opportunity to work on a variety of cutting-edge technologies & architectures at massive scale. Matthew holds an MS from Stanford in ML/AI & Robotics and is a thought-leader in the Jupyter community. He’s a core maintainer of many Jupyter and nteract projects such as papermill, and most recently testbook, and frequently presents related talks at conferences including PyCon, JupyterCon, & Spark Summit.

Open Data Science




Open Data Science
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Cambridge, MA 02142

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