Today, many organizations are looking to determine the optimal way to organize their data science talent.  This session will highlight common challenges facing organizations that maintain a decentralized data science organization model that ranges from duplication of work, high attrition, and lack of consistent development operations.  

This session will then highlight ways to establish common development operations practices, model review standards, and other specific techniques for building a strong data science community that effectively connects data scientists sitting in silos across disparate organizations.  These practices have yielded more significant results for the investment Red Hat has placed into data science over the last 2-3 years.


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