How to Lead in Data Science

Author:   Jike Chong ,  Yue Cathy Chang
Publisher:   Manning Publications
ISBN:  

9781617298899


Pages:   396
Publication Date:   09 March 2022
Format:   Paperback
Availability:   Available To Order   Availability explained
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How to Lead in Data Science


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Overview

To lead a data science team, you need to expertly articulate technology roadmaps, support a data-driven culture, and plan a data strategy that drives a competitive business plan. In this practical guide, you'll learn leadership techniques the authors have developed building multiple high-performance data teams. 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. Throughout, carefully crafted assessments and interview scenarios encourage introspection, reveal personal blind spots, and show development areas to help advance your career. 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.

Full Product Details

Author:   Jike Chong ,  Yue Cathy Chang
Publisher:   Manning Publications
Imprint:   Manning Publications
Dimensions:   Width: 18.50cm , Height: 3.00cm , Length: 23.40cm
Weight:   0.940kg
ISBN:  

9781617298899


ISBN 10:   1617298891
Pages:   396
Publication Date:   09 March 2022
Audience:   General/trade ,  General
Format:   Paperback
Publisher's Status:   Active
Availability:   Available To Order   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

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Reviews

“Improveleadership skills, irrespective of the domain you are in.” Vishwesh RaviShrimali “Whether you are new to managing, new to data science, or just want tobe a better advocate for your data team there are a lot of tips to improve yourpractice.” MichaelPetrey “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 datascience teams.” JesúsJuárez-Guerrero “Excellent book. Covers a large complex topic in a clear and understandableway.” GaryBake “Excellent and ambitious book that provides actionable insight on how tolead in data science. Filled with insightful vignettes, anecdotes, and casestudies to bring life and relevance to the frameworks and discussion.” MarcParadis


Improveleadership skills, irrespective of the domain you are in. Vishwesh RaviShrimali Whether you are new to managing, new to data science, or just want tobe a better advocate for your data team there are a lot of tips to improve yourpractice. MichaelPetrey 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 datascience teams. JesusJuarez-Guerrero Excellent book. Covers a large complex topic in a clear and understandableway. GaryBake Excellent and ambitious book that provides actionable insight on how tolead in data science. Filled with insightful vignettes, anecdotes, and casestudies to bring life and relevance to the frameworks and discussion. MarcParadis


Author Information

Dr. JikeChong 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 CathyChang 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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