From the course: Data Science Team Lifecycle Management

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Key principles for managing data scientists for a large company

Key principles for managing data scientists for a large company

From the course: Data Science Team Lifecycle Management

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Key principles for managing data scientists for a large company

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- Leading a successful data science team is challenging no matter the organization size, but large companies have a really unique set of challenges that are required, and a unique set of management skills that are also required. Let's look at a few of those challenges and how to deal with them. First, if you're working in a large company then you're likely working in a big data environment, and that often translates to added complexity. So as a manager in a large company, you may have to shift your focus from building models to managing data pipelines. This is because data-driven enterprises need to efficiently collect, move, and transform their data into actionable information as quickly as possible, and it's your job to ensure that happens. Secondly, being in a large company means spending more time managing the entire data scientist employee lifecycle including hiring, development, retention, backup resourcing, and…

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