Data science managers (and senior leaders who manage data science teams) must consider many questions about how to best execute their data science efforts. For example, what is the most effective way to lead a data science project?
How do I ensure that my data science team does not expose my organization to issues related to misuse of data and/or algorithms?
How do I validate the data science team's results?

This video provides a framework that managers can use to ensure a successful data science project. The focus of this framework is not on which specific algorithm a team should use, but rather on how to ensure data science efforts are effective and efficient.

Key aspects of the framework that will be discussed include:
1. Form data science teams
2. Establish processes for developing analytical solutions
3. Risk management

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