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This is a book that surpasses the boundaries of mining data and coding, but warns you about not forgetting them in the effort to successfully lead data science teams.
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A practical field guide for the unique challenges of data science leadership, filled with transformative insights, personal experiences, and industry examples.
In How to Lead in Data Science you'll master techniques for leading data science at every seniority level, from heading up a single project to overseeing a whole company's data strategy. You'll find advice on plotting your long-term career advancement, as well as quick wins you can put into practice right away.
In How to Lead in Data Science you'll master techniques for leading data science at every seniority level, from heading up a single project to overseeing a whole company's data strategy. You'll find advice on plotting your long-term career advancement, as well as quick wins you can put into practice right away.
about the technology
Leading a data science team takes more than the typical set of business management skills. You need specific know-how to articulate technology roadmaps, support a data-driven culture, and plan a data strategy that drives a competitive business plan. Whether you're looking to manage your team better or work towards a seat at your company’s top leadership table, this book will show you how.about the book
How to Lead in Data Science teaches strategies for thriving in data leadership and advancing your career in this competitive field. In this practical guide, authors Jike Chong and Yue Cathy Chang share leadership techniques that they've developed building multiple high-performance data teams.You'll learn best practices for balancing trade-offs, planning projects from vague requirements, and navigating roadblocks in company management structure. Blending insights from the author's hard-won experience with the timeless teachings of Aristotle and Confucius, this book will help you cultivate yourself, your team, and your company's data culture—all while driving the impact of data science in your organization. Throughout, carefully crafted assessments and interview scenarios encourage introspection, reveal personal blind spots, and show development areas to help advance your career.
what's inside
- 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
about the reader
For data practitioners looking to take their careers into project and people leadership, up to the executive level.about the author
Dr. Jike Chong and Yue Cathy Chang have both built, led, and grown multiple high-performing data teams. Dr. Chong developed the Yiren Digital Ltd. data team from the ground up, expanded and led the data team as chief data scientist at Acorns, and recently led the Hiring Marketplace Data Science team at LinkedIn. Yue Cathy Chang and her team "parachuted" into companies to address challenging and meaningful data needs. She has worked with leaders of centralized and distributed data teams at organizations big and small, including large asset-management firms and Fortune 50 companies.
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There are helpful examples, lists, and tools to use for evaluating data leadership and projects. It could help in providing common language to use across your organization or team.
It is not a book for aspiring data scientists but for seasoned data scientist with aspirations. I highly recommend it.
Excellent book. Covers a large complex topic in a clear and understandable way.
In our team we also have very different backgrounds and aspirations and there is something in for everyone, especially since we still work on our methodologies.
