How to Lead in Data Science
- 10h 17m
- Jike Chong, Yue Cathy Chang
- Manning Publications
- 2021
In How To Lead in Data Science you will learn:
- Best practices for leading projects while balancing complex trade-offs
- Specifying, prioritizing, and planning projects from vague requirements
- Navigating structural challenges in your organization
- Working through project failures with positivity and tenacity
- Growing your team with coaching, mentoring, and advising
- Crafting technology roadmaps and championing successful projects
- Driving diversity, inclusion, and belonging within teams
- Architecting a long-term business strategy and data roadmap as an executive
- Delivering a data-driven culture and structuring productive data science organizations
How to Lead in Data Science is full of techniques for leading data science at every seniority level—from heading up a single project to overseeing a whole company's data strategy. Authors Jike Chong and Yue Cathy Chang share hard-won advice that they've developed building data teams for LinkedIn, Acorns, Yiren Digital, large asset-management firms, Fortune 50 companies, and more. You'll find advice on plotting your long-term career advancement, as well as quick wins you can put into practice right away. Carefully crafted assessments and interview scenarios encourage introspection, reveal personal blind spots, and highlight development areas.
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
About the technology
Lead your data science teams and projects to success! To make a consistent, meaningful impact as a data science leader, you must articulate technology roadmaps, plan effective project strategies, support diversity, and create a positive environment for professional growth. This book delivers the wisdom and practical skills you need to thrive as a data science leader at all levels, from team member to the C-suite.
About the book
How to Lead in Data Science shares unique leadership techniques from high-performance data teams. It’s filled with best practices for balancing project trade-offs and producing exceptional results, even when beginning with vague requirements or unclear expectations. You’ll find a clearly presented modern leadership framework based on current case studies, with insights reaching all the way to Aristotle and Confucius. As you read, you’ll build practical skills to grow and improve your team, your company’s data culture, and yourself.
In this Book
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Foreword
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About the Cover Illustration
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What Makes a Successful Data Scientist?
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Capabilities for Leading Projects
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Virtues for Leading Projects
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Capabilities for Leading People
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Virtues for Leading People
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Capabilities for Leading a Function
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Virtues for Leading a Function
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Capabilities for Leading a Company
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Virtues for Leading a Company
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Landscape, Organization, Opportunity, and Practice
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Leading in Data Science and a Future Outlook
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Epilogue
