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Managing Data Science

You're reading from   Managing Data Science Effective strategies to manage data science projects and build a sustainable team

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Product type Paperback
Published in Nov 2019
Publisher Packt
ISBN-13 9781838826321
Length 290 pages
Edition 1st Edition
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Author (1):
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Kirill Dubovikov Kirill Dubovikov
Author Profile Icon Kirill Dubovikov
Kirill Dubovikov
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Toc

Table of Contents (18) Chapters Close

1. Section 1: What is Data Science? FREE CHAPTER
2. What You Can Do with Data Science 3. Testing Your Models 4. Understanding AI 5. Section 2: Building and Sustaining a Team
6. An Ideal Data Science Team 7. Conducting Data Science Interviews 8. Building Your Data Science Team 9. Section 3: Managing Various Data Science Projects
10. Managing Innovation 11. Managing Data Science Projects 12. Common Pitfalls of Data Science Projects 13. Creating Products and Improving Reusability 14. Section 4: Creating a Development Infrastructure
15. Implementing ModelOps 16. Building Your Technology Stack 17. Conclusion 18. Other Books You May Enjoy

Leadership and people management

In the Achieving the team Zen section, we concluded that a team leader should not be at the core of the team because this situation leads to severe organizational imbalance. Nonetheless, a team leader should be everywhere and nowhere at the same time. A team leader should facilitate team functioning, help every team member take part in the process, and mitigate any risks that threaten to disrupt the team functions before they become real issues. A good team leader can substitute and provide support for all or most of the roles in their team. They should have good expertise regarding the core roles of the team so that they can be helpful in as many of the team activities as possible.

The team leader should make sure that information propagates through the team effortlessly, and that all communication takes place as needed. If we take the internet...

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